Rahul specializes in writing IaC using Terraform. He is a full-stack java developer focused on continuous delivery and automation. 

All posts by Rahul Wagh - DevOps Expert

Rahul Wagh

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DevOps focus on eliminating the organizational silos that impede collaboration between development and operations functions, whereas SRE works to design and implement the kind of scalable, dependable systems that ensure maximum reliability. 
This blog post delves into the differences between DevOps and SREs, their roles and responsibilities, the problems they solve, and the tools they use.

While DevOps is all about what aspect of the matters, SRE talks about the how part of it all. Nevertheless, there are a few other differences between the two. 
<ol>
<li style="font-weight: 400;" aria-level="1">Implementing New Features – DevOps is responsible for implementing the new features request to a product, whereas SREs ensure those new changes don’t increase the overall failure rates in production.</li>
<li style="font-weight: 400;" aria-level="1">Process Flow – A DevOps team has a perspective of the development environment to put changes from development to production. On the other hand, SREs have a perspective of production, so they can make suggestions to the development team to limit the failure rates despite the new changes.</li>
<li style="font-weight: 400;" aria-level="1">Focus – DevOps’s primary focus is on continuity and speed of product development, whereas SRE’s main focus is on the system’s reliability, scalability, and availability.</li>
<li style="font-weight: 400;" aria-level="1">Team Structure – A typical DevOps team consists of professionals with dedicated roles and responsibilities such as – Product Owner, Team Lead, Cloud Architect, Software Developer, QA Engineer, Release Manager, System Administrator. In contrast, SREs have a team of engineers with operational and development skills set.</li>
</ol>

Although there is some overlap in the job roles of SREs and DevOps, there is wide segregation of functions:
<table>
<tbody>
<tr>
<td></td>
<td>DevOps</td>
<td>SREs</td>
</tr>
<tr>
<td>
Role
&nbsp;</td>
<td>The main role of the DevOps team is to solve the development problem, build solutions to cater to business requirements.
&nbsp;</td>
<td>SREs’ main role is to deal with operational problems, for example – production failures, infrastructure issues (disk, memory), security, monitoring.
&nbsp;</td>
</tr>
<tr>
<td>Focus
&nbsp;</td>
<td>Focus on product development with Continuous Integration/ Continuous Delivery.
&nbsp;</td>
<td>SREs put more focus on resilience, scaling, reliability, uptime, and robustness.
&nbsp;</td>
</tr>
<tr>
<td>Tools
&nbsp;</td>
<td>In the DevOps role, the most widely used tools are – Integrated Development Environment (IDEs) for development purposes, <a href="https://spacelift.io/blog/terraform-jenkins" target="_blank" rel="noopener">Jenkins</a> for Continuous Integration and Development, JIRA for change management, Splunk for log monitoring, SVN, GitHub.
&nbsp;</td>
<td>In the SRE role, the most widely used tools are Prometheus and Grafana for collecting and visualizing the different metrics (CPU usage, memory, disk space, etc.), incident alert tools (OP5, PageDuty, xMatters, etc.), Ansible, Puppet, or Chef, Kubernetes and Docker for container orchestration, cloud platform AWS, GCP, Azure, JIRA, SVN, GitHub.
&nbsp;</td>
</tr>
<tr>
<td>Bug reporting
&nbsp;</td>
<td>DevOps team is responsible for debugging the code in case of any bug reported in the end product.
&nbsp;</td>
<td>The SRE team is responsible for reporting the bug to the Core development team and does not get involved in debugging unless it is a production outage. SRE team is also responsible for debugging and fixing the infrastructure issues.
&nbsp;</td>
</tr>
<tr>
<td>Measurement metrics
&nbsp;</td>
<td>Typical measurement metrics for the DevOps role are Deployment Frequency and the Deployment Failure rate.
&nbsp;</td>
<td>Typical measurement metrics for the SRE role are Error Budgets, SLOs (Service Level Objective), SLIs (Service Level Indicator), SLAs (Service Level Agreement).
&nbsp;</td>
</tr>
<tr>
<td>Incident handling
&nbsp;</td>
<td>DevOps teams work on the incident feedback to mitigate the issue.</td>
<td>Conductsthe Post-Incident reviews to identify the root cause and document the findings to provide feedback to the core development team.</td>
</tr>
</tbody>
</table>

<ul>
<li><a href="https://spacelift.io/blog/ci-cd-tools" target="_blank" rel="noopener">Top Most Useful CI/CD Tools for DevOps</a></li>
<li><a href="https://spacelift.io/blog/devops-best-practices" target="_blank" rel="noopener">16 DevOps Best Practices for 2023</a></li>
<li><a href="https://spacelift.io/blog/terraform-in-ci-cd" target="_blank" rel="noopener"><span data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;How to Deploy your Infrastructure in CI/CD using Terraform&quot;}" data-sheets-userformat="{&quot;2&quot;:513,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0}">How to Deploy your Infrastructure in CI/CD using Terraform</a></li>
</ul>

Implementing the DevOps practices can reduce the friction between Development and Operations teams. It can also help you deliver the end product reliably along with other challenges and problems that the DevOps teams can solve.
<h3>1. Reduced Cost of Development and Maintenance</h3>
A DevOps team always works towards CI/CD, putting more effort into automated testing rather than manual testing and improving release management by automating it all.
As for the traditional Software Development Life Cycle, there is always toil on the effort (development, testing, release), which increases the overall cost for the product development and production maintenance. Putting DevOps practice in execution can significantly reduce the delivery time, development, and maintenance costs.
<h3>2. Shorter Release Cycle</h3>
One of the most effective changes a DevOps team brings is to deliver faster with a shorter release cycle. The reason why the DevOps team advocates a shorter release cycle is that it is easy to manage and roll back to the stable version in case there are any issues. 
As opposed to the traditional release cycles, where the focus is on getting everything delivered in one release, which increases the risk of failure in production and is much harder to roll back. If DevOps practices are followed strictly, the organization will always have a proper release version system with release versions and minimal manual interventions with the release artifacts.
Here are the gains of a shorter release cycle:
<ol>
<li style="font-weight: 400;" aria-level="1">Deliver the new change request more frequently;</li>
<li style="font-weight: 400;" aria-level="1">Pushing the upgrades (bug fixes, security patches, version upgrades) to production is much easier.</li>
</ol>
<h3>3. Automated and Continuous Testing</h3>
In contrast to the traditional development cycle, where the testing team has to wait for the delivery of the product in the test environment to begin the testing DevOps, testing is injected from the beginning of the development lifecycle.
DevOps facilitates continuous and automated testing with the help of the CI/CD tool (Jenkins) and version control (Git, BitBucket). Adequate coverage of functional, nonfunctional, and interaction tests running in the <a href="https://spacelift.io/blog/ci-cd-pipeline" target="_blank" rel="noopener">pipelines</a> can significantly improve the testing automation aspects of the project.
To learn more about DevOps, see our article on <a href="https://spacelift.io/blog/who-is-devops-engineer" target="_blank" rel="noopener">Who is DevOps?</a>

<h3>1. Reduced Mean Time to Recovery (MTTR)</h3>
SRE team is responsible for keeping the production up and running. In the event of a bug or production failure, SRE teams can roll back to the previous stable version of a product so that Mean Time to Recovery (MTTR) is reduced.
<h3>2. Reduced Mean Time to Detect (MTTD)</h3>
The other problem that the SRE team is trying to solve is to reduce the Mean Time to Detect(MTTD) using the <a href="https://spacelift.io/blog/kubernetes-deployment-strategies#canary-deployments" target="_blank" rel="noopener">Canary Rollouts</a> so that the new release is made available to a small group of users before doing full rollouts. Canary rollouts help the SRE team find the issues in the early stage with a limited number of affected users.
<h3>3. Automated Everything</h3>
Automation is one of the biggest challenges the SRE team has to face. It is often observed that rollouts and supporting tasks are carried out manually, leading to inconsistency and increasing the probability of human error. 
A good practice for managing the infrastructure is to use <a href="https://spacelift.io/blog/infrastructure-as-code" target="_blank" rel="noopener">Infrastructure as Code (IaC)</a> with the help of Terraform, Pulumi, and the automation tools such as Ansible, Puppet, Chef. SRE team can leverage those tools to solve the problem of automation.
<h3>4. Automated Functional and Non Functional Testing in Production</h3>
The Core Development team can automate functional and non-functional testing in the test and stage environments but not in production.
Reliability engineers can help implement automation testing on Production environments without affecting the end-user.
<h3>5. On-Calls and Incident Documentation</h3>
Often reliability engineers have to take the on-call duties for managing unforeseen incidents, but they also have to prepare the documentation of the incidents and the troubleshooting steps so that it can help others perform the on-call duties. 
The SRE team can build up a valuable knowledge base on incidents to improve the incident troubleshooting time.
<h3>6. Shared Knowledge</h3>
Gaining exposure and building the knowledge base of the product development ecosystem (dev, test, stage, prod) is always beneficial for reliability engineers to foresee the issues in the production environment. 
But the main problem arises when the knowledge base is outdated, automation playbooks have irrelevant comments. Regular knowledge base updates by SREs in collaboration with DevOps can fill the knowledge gap between the teams.

When we talk about the tools of DevOps and SRE, it is often observed that most of the tools are being used commonly by both DevOps and SREs. 
<h3>Common Tools</h3>
<h4>Planning</h4>
<ul>
<li style="font-weight: 400;" aria-level="1">Jira Software</li>
<li style="font-weight: 400;" aria-level="1">Confluence</li>
<li style="font-weight: 400;" aria-level="1">Slack</li>
<li style="font-weight: 400;" aria-level="1">Microsoft Teams</li>
</ul>
<h4>Configuration Management Tools</h4>
<ul>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/what-is-terraform" target="_blank" rel="noopener">Terraform</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/what-is-pulumi" target="_blank" rel="noopener">Pulumi</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/ansible-tutorial" target="_blank" rel="noopener">Ansible</a></li>
<li style="font-weight: 400;" aria-level="1">Puppet</li>
<li style="font-weight: 400;" aria-level="1">Chef</li>
</ul>
<h4>Version Management</h4>
<ul>
<li style="font-weight: 400;" aria-level="1">GitHub</li>
<li style="font-weight: 400;" aria-level="1">BitBucket</li>
<li style="font-weight: 400;" aria-level="1">GitLab</li>
</ul>
<h4>Log Monitoring</h4>
<ul>
<li style="font-weight: 400;" aria-level="1">Splunk</li>
</ul>
<h3>DevOps Tools</h3>
<h4>Continuous Integration Continuous Delivery</h4>
<ul>
<li style="font-weight: 400;" aria-level="1">Jenkins</li>
<li style="font-weight: 400;" aria-level="1">AWS CodePipeline</li>
</ul>
<span data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;Added: See our list of the most useful CI/CD tools that define the state of today’s software automation.&quot;}" data-sheets-userformat="{&quot;2&quot;:513,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0}">See our <a href="https://spacelift.io/blog/ci-cd-tools" target="_blank" rel="noopener">list of the most useful CI/CD tools</a> that define the state of today’s software automation. And take a look at <a href="https://spacelift.io/ci-cd-for-infrastructure" target="_blank" rel="noopener">Spacelift</a>, which is a sophisticated CI/CD platform for IaC that enables Gitops on infrastructure provisioning workflows. It provides a platform to manage IaC in an automated, easy, controlled, and secure manner. Spacelift goes above and beyond the support that is offered by the plain backend system.
<h4>Integrated Development Environment</h4>
<ul>
<li style="font-weight: 400;" aria-level="1">Intellij </li>
<li style="font-weight: 400;" aria-level="1">Visual Studio</li>
<li style="font-weight: 400;" aria-level="1">Sublime</li>
</ul>
<h4>Automated and Security Testing</h4>
<ul>
<li style="font-weight: 400;" aria-level="1">Jmeter</li>
<li style="font-weight: 400;" aria-level="1">Robot Framework</li>
<li style="font-weight: 400;" aria-level="1">Burp</li>
<li style="font-weight: 400;" aria-level="1">Wireshark</li>
</ul>
<h3>SRE Tools</h3>
<h4>Monitoring</h4>
<ul>
<li style="font-weight: 400;" aria-level="1">Kibana</li>
<li style="font-weight: 400;" aria-level="1">Prometheus</li>
<li style="font-weight: 400;" aria-level="1">Grafana</li>
<li style="font-weight: 400;" aria-level="1">New Relic</li>
<li style="font-weight: 400;" aria-level="1">Istio</li>
</ul>
<h4>Incident Reporting System</h4>
<ul>
<li style="font-weight: 400;" aria-level="1">PagerDuty</li>
<li style="font-weight: 400;" aria-level="1">OP5</li>
<li style="font-weight: 400;" aria-level="1">Opsgenie</li>
<li style="font-weight: 400;" aria-level="1">VictorOps</li>
</ul>

While the two share some core values, the focus of their work is different &#8211; the application lifecycle through DevOps and operations lifecycle management through SRE. Nevertheless, they both connect the Development and Operation teams while sharing similar responsibilities. And they are both working towards the same goal &#8211; enhancing the release cycle and achieving better product reliability.

Spacelift is an alternative to using homegrown solutions on top of a generic CI. It helps overcome common state management issues and adds several must-have capabilities for infrastructure management.

How to Become a DevOps Engineer in Six Months

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What does DevOps do? And what about SRE? See our article and find out the differences between DevOps and SRE. 

56-sre-vs-devops

SRE vs DevOps

SRE vs. DevOps: What’s the Difference Between Them?

Want to level up your Terraform knowledge? Explore our tutorials and step-by-step guides written by Terraform experts. Learn Terraform best practices and solutions to the most difficult problems.

Terraform Guides and Tutorials | Spacelift Blog

Terraform

Serverless applications are getting popular among the DevOps community because you do not have to worry about the application server infrastructure. <dfn>AWS Lambda</dfn> is an event-driven offering from AWS which can help you to run any application without the need for application servers.
In this blog post we will talk about AWS Lambda and how to use Terraform to manage AWS Lambda functions.
Terraform provides the <a href="https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/lambda_function" target="_blank" rel="nofollow noopener">aws_lambda_function</a> resource for managing the AWS Lambda functions. Although you can create and run Lambda functions from the AWS web console, <a href="https://spacelift.io/blog/what-is-terraform" target="_blank" rel="noopener">Terraform is a great tool</a> for managing Lambda functions via IaC (Infrastructure as Code. See more here: <a href="https://spacelift.io/blog/infrastructure-as-code" target="_blank" rel="noopener">What is Infrastructure as Code? Examples</a>).
In this tutorial, we will start with the basics of the AWS Lambda function and then we will deploy a very basic python app using AWS Lambda.
<h3>Table of Content:</h3>
<ul>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-lambda#what-is-aws-lambda-used-for">What is AWS Lambda used for?</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-lambda#prerequisites">Prerequisites</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-lambda#1-set-up-the-iam-roles-and-policies">Setting up the IAM Roles and Policies</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-lambda#2-write-the-python-application">Writing the Python application</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-lambda#3-create-a-zip-of-python-application">Creating a ZIP of Python Application</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-lambda#4-add-awslambdafunction-function">Adding aws_lambda_function</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-lambda#5-run-and-execute-terraform-maintf">Running and Executing Terraform main.tf</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-lambda#5-run-and-execute-terraform-maintf">Verifying the Lambda function from AWS console</a></li>
</ul>

<a href="https://aws.amazon.com/lambda/" target="_blank" rel="nofollow noopener">AWS Lambda function</a> is very flexible and supports various use cases:
<ol>
<li style="font-weight: 400;" aria-level="1">Event driven applications—AWS Lambda can be triggered from a number of different event sources. Examples include triggering when a database row is updated, and triggering when the message count in a queue is greater than a certain number.</li>
<li style="font-weight: 400;" aria-level="1">Web and mobile backends—For a Mobile touchscreen, GUI event can be integrated with AWS Lambda using AWS API Gateway to trigger the Lambda function by calling the microservice-http-endpoint.</li>
<li style="font-weight: 400;" aria-level="1">Machine learning and data processing—As AWS Lambda supports Python, it is well suited for machine learning as well as data analytics applications, because ML and Data Analytics applications rely heavily on Python and its libraries (Numpy, TensorFlow, MatPlotlib Scipy etc.)</li>
</ol>

Let&#8217;s start with the prerequisites for this tutorial.
<ol>
<li style="font-weight: 400;" aria-level="1">You should have <a href="https://learn.hashicorp.com/tutorials/terraform/install-cli" target="_blank" rel="nofollow noopener">Terraform installed</a> onto your machine (see our tutorial here: <a href="https://spacelift.io/blog/how-to-install-terraform" target="_blank" rel="noopener">How to Download and Install Terraform on Windows, Linux &amp; macOS</a>) </li>
<li style="font-weight: 400;" aria-level="1">You must have an AWS account. </li>
</ol>
Before proceeding further, make sure Terraform is installed by running the command – $ terraform -version

image10-4

$ terraform -version

Now, here’s how to manage AWS Lambda functions:

The next step is to set up an <a href="https://spacelift.io/blog/aws-iam-roles" target="_blank" rel="noopener">IAM Role</a> for your Lambda function, along with any policies that the Lambda function requires. The exact policies required will depend on what your function does, and what services it needs to access. Since this article is mainly focused on explaining how to manage Lambda functions via Terraform, we will keep the IAM Roles and Policies very basic.
<h3>Create main.tf and add IAM Role</h3>
Let’s start by creating a main.tf file and inside the main.tf file create a role Spacelift_Test_Lambda_Function_Role.

<h3>Add IAM Policy</h3>
After creating the IAM Role, let’s create an <a href="https://spacelift.io/blog/iam-policy" target="_blank" rel="noopener">IAM Policy</a> to manage the permissions associated with the role. As this is a basic application, we will be assigning the following permissions: 
<ol>
<li style="font-weight: 400;" aria-level="1">logs:CreateLogGroup</li>
<li style="font-weight: 400;" aria-level="1">logs:CreateLogStream</li>
<li style="font-weight: 400;" aria-level="1">logs:PutLogEvents</li>
</ol>
Add the following IAM Policy resource block to main.tf:

<h3>Attach IAM Policy to IAM Role</h3>
Now that we have created an IAM Policy and IAM Role for the Terraform managed AWS Lambda function, let’s attach both IAM Policy and IAM Role to each other:

Read more about <a href="https://spacelift.io/blog/terraform-iam-policy" target="_blank" rel="noopener">Creating IAM Policies with Terraform</a>.

Since the IAM Role and IAM Policy have now been created, let’s call on the Python application which we will be running on AWS Lambda.
<ol>
<li style="font-weight: 400;" aria-level="1">Create a directory python parallel to main.tf.</li>
<li style="font-weight: 400;" aria-level="1">Inside the directory python, create a file index.py.</li>
<li style="font-weight: 400;" aria-level="1">Add the following python function to it:</li>
</ol>

As in the previous step, we have created a python file index.py. Now, we need to create a ZIP file because <code>aws_lambda_function</code> needs the code to be stored in a ZIP file in order to upload to AWS.
This ZIP file we are going to upload and submit to AWS Lambda function:

<ul>
<li><a href="https://spacelift.io/blog/5-ways-to-manage-terraform-at-scale" target="_blank" rel="noopener">5 Ways to Manage Terraform at Scale</a></li>
<li><a href="https://spacelift.io/blog/terraform-automation" target="_blank" rel="noopener">How to Automate Terraform Deployments and Infrastructure Provisioning</a></li>
<li><a href="https://spacelift.io/blog/how-specialized-solution-can-improve-your-iac" target="_blank" rel="noopener">How to Improve Your Infrastructure as Code using Terraform</a></li>
</ul>

Alright. Now we have everything (IAM Role, IAM Policy, Python Code) in place. Let’s write down the aws_lambda_function resource block:

Here are a few things you should keep in mind while writing aws_lambda_function resource block:
<ul>
<li style="font-weight: 400;" aria-level="1">Runtime—You should mention correction runtime which AWS Lambda is going to use for running your Lambda function. Currently, AWS Lambda supports Node.js, Python, JAVA, Ruby, Go, .NET.</li>
<li style="font-weight: 400;" aria-level="1">IAM Role—Always mention the correct IAM role which you have created for the Lambda function.</li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-depends-on" target="_blank" rel="noopener">Depends_on</a>—Mention the correct IAM policy attachment block where you have attached the IAM role to IAM policy. It is a sanity check to make sure that IAM Policy and IAM roles are in place before lambda function is created.</li>
</ul>

Here is the complete main.tf file:

Let&#8217;s run the following commands in sequence:
1. $ <a href="https://spacelift.io/blog/terraform-init" target="_blank" rel="noopener">terraform init</a>

image1-1

terraform init

image6-1

terraform plan

Here is the remaining output of terraform plan:

image8-5

terraform plan output

image9-1

terraform apply

Here is the remaining output of terraform apply :

image2-1

terraform apply output

Let’s head over to AWS Console and do the test run. From the AWS dashboard you can start by searching Lambda from the search bar:

image4-9

AWS Console search

Click on Lambda to see the Lambda function we have provisioned using Terraform:

image11-4

AWS Console Lambda

Click on it, then use the Test button to run the Lambda function:

image7-5

Testing lambda function

A new window will open where you need to specify the event name. As you can see in the below pic name, I have assigned the event name as MyCustomMessage and entered a custom message as key1.

image5-9

MyCustomMessage

Now, click on the Test tab and then on the orange Test Button:

image12-3

test tab

As you can see, it has returned the message Hello Spacelift, which we have written inside the python file.

image3-10

test message

This article is meant to get you familiar with using Terraform to manage AWS Lambda functions. Although the article uses Python, you can use other programming languages such as GO, Java, Ruby, .NET to satisfy your business needs. The core concepts of setting AWS Lambda with Terraform still remain the same regardless of your language choice.
We encourage you also to explore <a href="https://spacelift.io/terraform-at-scale" target="_blank" rel="noopener">how Spacelift makes it easy to work with Terraform</a>. If you need any help managing your Terraform infrastructure, building more complex workflows based on Terraform, and managing AWS credentials per run, instead of using a static pair on your local machine, Spacelift is a fantastic tool for this. It supports Git workflows, policy as code, programmatic configuration, context sharing, drift detection, and many more great <a href="https://spacelift.io/blog/how-specialized-solution-can-improve-your-iac" target="_blank" rel="noopener">features</a> right out of the box.

Spacelift effectively manages Terraform state, more complex workflows, supports policy as code, programmatic configuration, context sharing, drift detection, resource visualization and includes many more features.

Grab our ultimate cheat sheet PDF for all the Terraform functions you need on hand.

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Debugging and logging are the lifeline of developers when it comes to troubleshooting any kind of issue. If something has failed in a production environment, developers always look for the application logs which can give them the type, cause, and time of the error. 
The exact same principle is also followed when debugging the Terraform script. Terraform projects can grow very quickly when worked on by multiple teams. If you do not have a proper logging setup for troubleshooting, the project team will have a very difficult time troubleshooting and debugging.
In this article, we will focus on the commonly followed practices for debugging Terraform Projects. 
How to enable the logs for debugging? How to set the log file for debugging? How to manage log levels? Here’s how.

The only prerequisite we have for this blog post is you must <a title="install Terraform on your host machine" href="https://spacelift.io/blog/how-to-install-terraform" target="_blank" rel="noopener">install Terraform on your host machine</a>.
You can verify your Terraform installation by running the following <a title="Terraform version" href="https://spacelift.io/blog/terraform-version-upgrade" target="_blank" rel="noopener">Terraform version</a> command:

There are certain <a title="log levels" href="https://www.terraform.io/internals/debugging" target="_blank" rel="nofollow noopener">log levels</a> provided by Terraform for debugging and troubleshooting. As developers, we have to choose and set the log level for our Terraform project.
<h3>Types of Log Level</h3>
In total, there 5 log levels which can be used for debugging purposes: 
<ul>
<li style="font-weight: 400;" aria-level="1">TRACE—one of the most descriptive log levels, if you set the log level to TRACE, Terraform will write every action and step into the log file.</li>
</ul>
<ul>
<li style="font-weight: 400;" aria-level="1">DEBUG—a little bit more sophisticated logging which is used by developers at critical or more complex pieces of code to reduce debugging time.</li>
</ul>
<ol>
<li style="list-style-type: none;">
<ol>
<li style="font-weight: 400;" aria-level="1">INFO—the info log level is useful when needing to log some informative instructions or readme type instructions.</li>
<li style="font-weight: 400;" aria-level="1">WARN—used when something is not critical but would be nice to include in the form of a log so that the developer can make adjustments later.</li>
</ol>
</li>
</ol>
<ul>
<li aria-level="1">ERROR—as the name suggests, this is used if something is terribly wrong and is a blocker.</li>
</ul>
<h3>How to set the log level?</h3>
The log level can be set with the environment variable TF_LOG. You need to export the variable with the correct log level. Here is an example of where TF_LOG is set with DEBUG level:

Verify the log level:

After setting the log level, the next thing we need to set is the Log File Path, and for that we are going to use the environment variable TF_LOG_PATH.
For this blog post we are going to create a log file named terraform-debug.log.
We are going to place this file under the directory /home/vagrant/terraform-ec2-aws.
*Note – You can name and choose the log file path as per your requirement.
Let’s export the TF_LOG_PATH

Now, after setting both Log Level and Log File path, let’s create a very small Terraform project to start an AWS EC2 instance.
Here is my main.tf:

Apply the above Terraform configuration by running the following commandterraform applys: 
<ol>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-init" target="_blank" rel="noopener"><code>terraform init</code></a></li>
<li style="font-weight: 400;" aria-level="1"><code><a href="https://spacelift.io/blog/terraform-apply" target="_blank" rel="noopener">terraform apply</a></code></li>
</ol>
After successful execution of the above Terraform code, let’s verify the debug logs available at /home/vagrant/terraform-ec2-aws/terraform-debug.log.
Here is the screenshot taken from the terraform-debug.log file which shows the DEBUG logs along with the INFO logs:

image1-10

DEBUG logs and the INFO logs

Here are some sample logs from the terraform-debug.log:

Now that we have seen in the previous section on how to set up the TF_LOG and TF_LOG_PATH, let’s take a look at an example of how to put some <a title="custom validation" href="https://www.terraform.io/language/values/variables#custom-validation-rules" target="_blank" rel="nofollow noopener">custom validation</a> on the <a title="Terraform variable" href="https://spacelift.io/blog/how-to-use-terraform-variables" target="_blank" rel="noopener">Terraform variable</a>, and to see if the validation fails. For this, we are going to log an error_message.
Validation condition: Provision of the EC2 instance should be restricted to t2.nano, t2.micro, t2.small. If the developer wants to provision the t2.medium or any other higher instance, we should restrict the developer with the proper error messages.
Here is a Terraform script with a validation and error_message:

If you look carefully into the variable resource:
<ol>
<li style="font-weight: 400;" aria-level="1">condition:  We have defined the regex to allow only – t2.nano, t2.micro, t2.small</li>
<li style="font-weight: 400;" aria-level="1">error_message: We have set up an error message stating “Invalid Instance Type name. You can only choose – t2.nano,t2.micro,t2.small”</li>
</ol>
So, when the user tries to supply t2.medium then they should get the following error message:

image2-10

error message

This post is all about making yourself aware of the debugging and logging features provided by Terraform for troubleshooting the issues which you might face in your development, testing, staging, or production instances.
Setting up the correct info, debug and error message can significantly lessen your troubleshooting time as well as make your monitoring task. You can even dump the Terraform logs into log analyzer tools such as Splunk or ELK to get some visual graphs.
We encourage you also to explore <a href="https://docs.spacelift.io/" target="_blank" rel="noopener">how Spacelift makes it easy to work with Terraform</a>. If you need any help managing your Terraform infrastructure, building more complex workflows based on Terraform, and managing AWS credentials per run, instead of using a static pair on your local machine, Spacelift is a fantastic tool for this. It supports Git workflows, policy as code, programmatic configuration, context sharing, drift detection, and many more great <a href="https://spacelift.io/blog/how-specialized-solution-can-improve-your-iac" target="_blank" rel="noopener">features right out of the box</a>. You can check it for free by <a href="https://spacelift.io/free-trial" target="_blank" rel="noopener">creating a trial account</a>.

Initialize/ plan/ apply your IaC, manage modules, state, and more. 

Terraform Functions, Expressions, Loops (Examples)

DRY in Terraform Configurations With Dynamic Blocks

How to Use Terraform Join and Split Functions with Strings

Learn how to debug Terraform projects and troubleshoot Terraform errors whether on Windows or other operating system. See how verify the debug logs.

47-debugging-terraform

Debug Terraform

How to Debug & Troubleshoot Terraform Projects: Tutorial

Amazon S3 Bucket is a storage service offered by AWS for storing data lakes, websites, mobile applications, backup and restore, archive, enterprise applications, etc. The S3 stands for Simple Storage Service which can be scaled based on individual or organization needs. On top of providing a storage solution, Amazon S3 also provides comprehensive access management which can help you to set up very granular-level permissions.
This blog post is all about managing the AWS S3 bucket using Terraform. Terraform provides three S3 resources: 
<ol>
<li style="font-weight: 400;" aria-level="1">aws_s3_bucket</li>
<li style="font-weight: 400;" aria-level="1">aws_s3_bucket_object</li>
<li style="font-weight: 400;" aria-level="1">aws_s3_bucket_public_access_block</li>
</ol>
These resources are used for managing the S3 bucket, but exhibit different characteristics which we will explore in this post.
AWS S3 bucket supports versioning, replication, encryption, ACL (access control list), and bucket object policy. Here is the list of S3 tasks which we are going to complete using Terraform: 
<ol>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-s3-bucket#1-set-up-aws-access-credentials">Setting up AWS Access Credentials (prerequisite).</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-s3-bucket#1-set-up-aws-access-credentials">Using aws_s3_bucket resource to create S3 Bucket.</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-s3-bucket#1-set-up-aws-access-credentials">Uploading files to S3 bucket using aws_s3_bucket_object.</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-s3-bucket#1-set-up-aws-access-credentials">Managing ACL (Access Control List) using aws_s3_bucket_public_access_block.</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://spacelift.io/blog/terraform-aws-s3-bucket#1-set-up-aws-access-credentials">Deleting the S3 bucket using Terraform.</a></li>
</ol>
Let’s start.

Terraform always needs Access Key and Secret Key to work with the AWS resources. But, AWS always provides you with static plain text credentials and should not be stored, as it is contained in your Terraform file. 
There are a couple of ways to handle this problem:
<ol>
<li style="font-weight: 400;" aria-level="1">Using Spacelift AWS Integration with <a href="https://spacelift.io/blog/aws-iam-roles" target="_blank" rel="noopener">IAM roles</a>. Spacelift provides AWS integration out of the box. Here is a comprehensive guide from Spacelift which can help to integrate with AWS: <a href="https://docs.spacelift.io/integrations/cloud-providers/aws" target="_blank" rel="noopener">AWS Integration Tutorial</a></li>
<li style="font-weight: 400;" aria-level="1">The second way would be generating AWS access credentials dynamically based on <a href="https://spacelift.io/blog/iam-policy" target="_blank" rel="noopener">IAM policies</a> and storing them into the <a href="https://www.vaultproject.io/docs/install" target="_blank" rel="nofollow noopener">Vault (Hashicorp Vault)</a>. Read more about <a href="https://spacelift.io/blog/terraform-iam-policy" target="_blank" rel="noopener">Creating IAM Policies with Terraform</a>.</li>
</ol>
The above-mentioned methods will help you integrate with AWS in a more secure way. 
<a href="https://docs.spacelift.io/integrations/cloud-providers/aws#programmatic-setup" target="_blank" rel="noopener">Spacelift Programmatic Setup of IAM Role</a> —If you are using Spacelift, then here is the code snippet of Terraform which you should integrate with your existing Terraform infrastructure code base.

Hashicorp Vault programmatic Setup—If you are using the Hashicorp vault, here’s the Terraform code snippet which defines the AWS IAM role for managing an S3 Bucket.

<ul>
<li><a href="https://spacelift.io/blog/terraform-in-ci-cd" target="_blank" rel="noopener"><span data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;Deploying Infrastructure in CI/CD with Terraform&quot;}" data-sheets-userformat="{&quot;2&quot;:513,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0}">Deploying Infrastructure in CI/CD with Terraform</a></li>
<li><a href="https://spacelift.io/blog/drift-detection" target="_blank" rel="noopener"><span data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;Infrastructure Drift Detection and How to Fix It&quot;}" data-sheets-userformat="{&quot;2&quot;:513,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0}">Infrastructure Drift Detection and How to Fix It</a></li>
<li><a href="https://spacelift.io/blog/how-specialized-solution-can-improve-your-iac" target="_blank" rel="noopener"><span data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;How to Improve Your Infrastructure as Code using Terraform&quot;}" data-sheets-userformat="{&quot;2&quot;:513,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0}">How to Improve Your Infrastructure as Code using Terraform</a></li>
</ul>

After setting up the credentials, let’s use the Terraform aws_s3_bucket resource to create the first S3 bucket.  
The S3 Bucket name we are going to use is – spacelift-test1-s3.
Here are the names of items needed for creating the S3 bucket: 
<ol>
<li style="font-weight: 400;" aria-level="1">region—Specify the name of the region.</li>
<li style="font-weight: 400;" aria-level="1">bucket—Name the bucket i.e. – spacelift-test1-s3.</li>
<li style="font-weight: 400;" aria-level="1">acl—Access control list. We will set the S3 access as private.</li>
</ol>
Create a Terraform file named – main.tf and use the following Terraform code snippet:

Along with main.tf, let’s create version.tf for AWS and vault version.

If you are going to use Hashicorp vault instead of Spacelift, then you must also add the Hashicorp vault version.

Let’s apply the above Terraform configuration using Terraform commands:
1. <code>$ terraform init</code> – This is the first command we are going to run.

image6-3

2.  <code>$ terraform plan</code> – The second command would be to run a Terraform plan. This command will tell you how many AWS resources are going to be added, changed or destroyed.

image1-4

$ terraform plan

3.  <code>$ terraform apply</code> – Apply the Terraform configuration using the Terraform apply command which will eventually create an S3 bucket in AWS.

image2-4

$ terraform apply

image7-3

AWS S3

In Step 2 we saw how to create an S3 bucket using the aws_s3_bucket Terraform resource.  In this step, we are going to use the same S3 bucket (spacelift-test1-s3) to upload files into. 
When we want to perform some additional operations (e.g. – upload files) on the S3 bucket then we are going to use the aws_s3_bucket_object Terraform resource.
For uploading the files to the S3 bucket we will extend the existing Terraform script from Step 2, along with the new aws_s3_bucket_object resource block.
We are going to upload the two sample text files:
<ol>
<li style="font-weight: 400;" aria-level="1">test1.txt</li>
<li style="font-weight: 400;" aria-level="1">test2.text</li>
</ol>
Here is the screenshot of my project structure for uploading files, which includes my main.tf along with test1.txt, test2.txt files.

image8-3

Terraform S3 bucket

As you can see from the project structure, I have kept my test files under the directory uploads, so I need to mention the relative path inside my Terraform file (main.tf).
Here is my Terraform file:

Here are some additional notes for the above-mentioned Terraform file – 
<ol>
<li style="font-weight: 400;" aria-level="1">for_each = fileset(“uploads/”, “*”) – <a href="https://spacelift.io/blog/terraform-for-loop" target="_blank" rel="noopener">For loop</a> for iterating over the files located under upload directory.</li>
<li style="font-weight: 400;" aria-level="1">bucket =  aws_s3_bucket.spacelift-test1-s3.id – The original S3 bucket ID which we created in Step 2.</li>
<li style="font-weight: 400;" aria-level="1">Key = each.value – You have to assign a key for the name of the object, once it’s in the bucket.</li>
<li style="font-weight: 400;" aria-level="1">Source = “uploads/${each.value}” – Path of the files which will be uploaded to the S3 bucket.</li>
</ol>
<h3>How to Apply the New Changes?</h3>
Since we are working in the same main.tf file and we have added a new Terraform resource block aws_s3_bucket_object, we can start with the Terraform plan command:
1. <code>$ terraform plan</code> – This command will show that 2 more new resources (test1.txt, test2.txt) are going to be added to the S3 bucket. Because we have previously created an S3 bucket, this time it will only add new resources.

image3-4

aws_s3_bucket_object

2. <code>$ terraform apply</code> – Run the Terraform apply command and you should be able to upload the files to the S3 bucket.

image4-4

aws_s3_bucket_object test

Here is the screenshot from AWS console S3 bucket:

image9-3

Spacelift-test1-s3

There are many more things that you can do with Terraform and the S3 Bucket. Here is a guide on <a href="https://spacelift.io/blog/how-to-rename-aws-s3-bucket-in-terraform" target="_blank" rel="noopener">how to rename an AWS S3 bucket in Terraform</a> which can help you rename your S3 bucket.

Now, after uploading the files to an S3 bucket, the next Terraform resource which we are going to talk about is aws_s3_bucket_public_access_block. This resource is going to help you manage the public access associated with your S3 bucket. 
By default, the value is false, which means we are allowing public ACL (Access Control List). If you want to restrict the public ACL, you have to set the value to true.
Here, we are going to take the same example which we have taken previously for uploading the files to an S3 bucket:

You can see in the above example that we have restricted the following public ACL: 
<ol>
<li style="font-weight: 400;" aria-level="1"> block_public_acls   = true</li>
<li style="font-weight: 400;" aria-level="1"> block_public_policy = true</li>
<li style="font-weight: 400;" aria-level="1"> ignore_public_acls  = true</li>
<li style="font-weight: 400;" aria-level="1"> restrict_public_buckets = true</li>
</ol>
With the help of aws_s3_bucket_public_access_block, you can manage the public access control list onto your S3 Bucket.

In the previous steps, we have seen how to create an S3 bucket and how to upload files to the S3 bucket using terraform aws_s3_bucket, aws_s3_bucket_object resources.
In this section, you will see how we can delete the S3 bucket once we are done working with the S3.
When you are using Terraform, the deletion part is always easy. You simply need to run the universal <a href="https://spacelift.io/blog/how-to-destroy-terraform-resources" target="_blank" rel="noopener"><code>$ terraform destroy</code></a> command and it will delete all the resources which you have created previously.

image5-3

$ terraform destroy

As you can see in the screenshot, Terraform has deleted the resources in the reverse chronological order starting from test2.txt, test2.txt, and finally the bucket spacelift-test1-s3.

Using Terraform to create an S3 bucket is relatively simple, but it is not recommended to use Terraform for uploading thousands of files into the S3 bucket. Terraform is an infrastructure provisioning tool and should not be used for performing data-intensive tasks. This blog is a comprehensive guide to getting yourself familiar with Terraform and the S3 bucket.
We encourage you also to explore <a href="https://docs.spacelift.io/" target="_blank" rel="noopener">how Spacelift makes it easy to work with Terraform</a>. If you need any help managing your Terraform infrastructure, building more complex workflows based on Terraform, and managing AWS credentials per run, instead of using a static pair on your local machine, Spacelift is a fantastic tool for this. It supports Git workflows, policy as code, programmatic configuration, context sharing, drift detection, and many more great <a href="https://spacelift.io/blog/how-specialized-solution-can-improve-your-iac" target="_blank" rel="noopener">features right out of the box</a>. You can check it for free, by <a href="https://spacelift.io/free-trial" target="_blank" rel="noopener">creating a trial account</a>.

If you are struggling with Terraform automation and management, check out Spacelift. It helps you manage Terraform state, build more complex workflows, and adds several must-have capabilities for end-to-end infrastructure management.

How to Manage Terraform S3 Backend - Best Practices

See how to create and manage an AWS S2 bucket using Terraform. Examples of Amazon Web Services S3 bucket in Terraform.

29-create-s3-bucket

Managing S3 Bucket using Terraform

Creating and Managing an AWS S3 Bucket Using Terraform

How to install and upgrade Terraform to the latest version

Just like a versioning tool such as Git or SVN, which allows you to rollback or upgrade if there is a problem with the current version of your code, <a href="https://spacelift.io/blog/tfenv" target="_blank" rel="noopener">tfenv</a> lets you upgrade as well as rollback versions of Terraform. 
But why do we need multiple versions of Terraform? A typical infrastructure setup always consists of development, testing, staging, and the production environment. As a rule of thumb, the production environment gets the most stable version. On the other hand, development, test, and sometimes staging environments receive newer versions of any software package. The same goes for Terraform. 
If during the testing phase there is a bug which breaks the existing infrastructure setup, tfenv can help roll back Terraform to the previous stable version. Similarly, you can upgrade to the next stable version so that your Terraform stack is up to date.
In this post, we will see how you can install Terraform, as well as how to upgrade it to a specific release version (Terraform v0.15, v0.14, v0.13, v0.12, or any other) using tfenv.

Before we go into the installation part of tfenv let’s first see what tfenv is.
tfenv is a versioning tool for Terraform, maintained by the open source community on <a href="https://github.com/tfutils/tfenv" target="_blank" rel="nofollow noopener">Github,</a> under the MIT Open source license. Keep in mind it is not an official tool by HashiCorp.
<h3>Installing tfenv on MacOS</h3>
Lets first see how we can install tfenv on MacOS. For MacOS we are going to use the brew package manager. Refer to the following command for installation: 
$ brew install tfenv
<h3>Installing tfenv on Linux</h3>
Installing on Linux is a bit more manual. Use the following installation instructions:
1: Clone the GitHub repo
$ git clone https://github.com/tfutils/tfenv.git ~/.tfenv
2: Update $PATH 
$ echo &#8216;export PATH=&#8221;$HOME/.tfenv/bin:$PATH&#8221;&#8216; &gt;&gt; ~/.bash_profile
3: Create a symlinks
$ sudo ln -s ~/.tfenv/bin/* /usr/local/bin
<h3>Installing tfenv on Windows</h3>
tfenv does not currently support Windows due to symlink issues. 
<h3>Verify tfenv installation</h3>
Whether you are on MacOS or Linux, you can verify the installation of tfenv by simply running the following command:
$ tfenv -v
It should return with the tfenv version. At the time of writing this article, the latest version of tfenv was tfenv 2.2.2

image10

installing tfenv on Linux

Now that we have seen how to install tfenv, let’s dig into the tfenv commands. The first command which we are going to see is 
 $ tfenv list-remote
The above command will list out all available versions of Terraform to date. Here’s a screenshot after running the tfenv list-remote command.

image1-2

tfenv list-remote

If you are looking for a specific version of <a href="https://spacelift.io/blog/what-is-terraform">Terraform</a> (e.g. v0.12, v0.13, v0.14, v0.15) but tfenv list-remote returns with a really long list of versions, you can run the following command that includes the version you want. In this example, I am looking for Terraform 0.12.0
$ tfenv list-remote | grep 0.12.0
&nbsp;

image11-2

$ tfenv list-remote | grep 0.12.0

<ul>
<li><a href="https://spacelift.io/blog/github-actions-terraform" target="_blank" rel="noopener"><span data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;Managing Terraform at Scale with Github Actions&quot;}" data-sheets-userformat="{&quot;2&quot;:513,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0}">Managing Terraform at Scale with GitHub Actions</a></li>
<li><a href="https://spacelift.io/blog/terraform-automation" target="_blank" rel="noopener">How to Automate Terraform Deployments</a></li>
<li><a href="https://spacelift.io/blog/how-specialized-solution-can-improve-your-iac" target="_blank" rel="noopener"><span data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;How to Improve Your Infrastructure as Code using Terraform&quot;}" data-sheets-userformat="{&quot;2&quot;:513,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0}">How to Improve Your Infrastructure as Code using Terraform</a></li>
</ul>

You have seen in the previous steps how to install tfenv and how to list all or some specific version of Terraform. 
Let’s install a specific version (0.12.0) of Terraform using tfenv. Use the following tfenv for installation: 
$ tfenv install 0.12.0

image6-2-2

$ tfenv install 0.12.0

After installing Terraform 0.12.0, you need to run one more command to actually use that version:
$ tfenv use 0.12.0

image3-2

$ tfenv use 0.12.0

Verify the installation of Terraform by running 
$ terraform -v

image13

$ terraform -v 

Note: the above-mentioned command can be used for any version of Terraform , e.g. 0.13.0, 0.14.0, 0.15.0

In the previous step we saw how to upgrade to a specific version of Terraform, but what if you want to upgrade to the latest version irrespective of any specific one?
Well, tfenv provides the latest flag which can be used along with the $ tfenv install command and it will let you install the latest stable version of Terraform.
Here is the tfenv command for installing the latest version of Terraform: 
$ tfenv install latest

image2-2

$ tfenv install latest

To switch and use the latest version of Terraform, run: 
$ tfenv use 1.0.8

image5-2-2

$ tfenv use 1.0.8

Verify the installation by running the $ terraform -v command:

image9-2

$ terraform -v

In the previous steps we have seen how to install specific versions (0.12.0) as well as the latest version of Terraform.
Let’s now see how to install and switch to some other version, 0.13.0 for example.
tfenv always mandates you to first install the version (if you have not installed before) of Terraform which you want to have, and then to make the switch to that specific version.
First, install Terraform version 0.13.0:
$ tfenv install 0.13.0

image7-2

$ tfenv install 0.13.0

Then, make the switch to 0.13.0 (if you have already installed other versions of Terraform, you can make direct use of the tfenv use command):
$ tfenv use 0.13.0

image8-2

$ tfenv use 0.13.0

Note: the above-mentioned steps can be used for switching to any desired version of Terraform. Learn more about how to manage different <a href="https://spacelift.io/blog/terraform-version" target="_blank" rel="noopener">Terraform versions</a>.

Last but not least, tfenv provides you with a feature to uninstall any version of Terraform. To uninstall any version of Terraform, you must provide the exact version (e.g. latest, 0.15.0, 0.14.0 etc.).
Here’s how to uninstall the latest version of Terraform:
$ tfenv uninstall latest

image4-2

$ tfenv uninstall latest

Learn how to install and upgrade Terraform to the latest version. A quick step-by-step tutorial to upgrading Terraform. Terraform installation made simple.

Rahul Wagh

SRE vs. DevOps: What’s the Difference Between Them?

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