Ankur Mandal

DevOps Infrastructure Automation: A Comprehensive Guide


Ankur Mandal

5 min read

Agility, efficiency, and scalability are paramount in our digital landscape. DevOps, a fusion of people and processes, has emerged as a transformative approach for deployment and development. 

However, as organizations grow, IT teams often grapple with increasing complexities. This underscores the importance of DevOps infrastructure automation that can speed up configuration, and eliminate quality or security issues.

In this blog, you will gain insights into the nuances of DevOps infrastructure automation. These insights will equip you with the tools and strategies to implement them in your environment, paving the way for continuous innovation and business growth.

DevOps represents a significant methodological shift that merges software development (Dev) with IT operations (Ops) to create a unified and cooperative approach. 

By combining elements of both development and operations, DevOps signals a fundamental change in how organizations handle their applications and infrastructure life cycle. Instead of having separate departments with specific duties, DevOps promotes a culture of shared ownership, continuous collaboration, and collective responsibility among teams. 

The integrated approach of DevOps aims to streamline processes, hasten delivery timelines, and boost overall flexibility, enabling organizations to more effectively meet evolving market demands and customer requirements.

Introduction To DevOps Infrastructure Automation

DevOps infrastructure automation is essential for organizations aiming to achieve agility, reliability, and innovation in their software delivery processes. Automating routine tasks, maintaining uniformity, and facilitating quick development cycles enables teams to deliver top-notch software faster and more efficiently, ultimately enhancing business outcomes.

DevOps Infrastructure automation enables developers and operations teams to efficiently manage resources through automation efficiently, reducing the need for manual configuration of hardware, software, and operating systems. 

The process, also known as programmable infrastructure, utilizes scripts to define and execute configuration tasks, paving the way for enhanced efficiency and agility in resource management. It offers the following benefits.

  • Efficiency and Agility: Automation expedites infrastructure provisioning, setup, and maintenance. This swift deployment empowers organizations to roll out software updates and introduce new features quickly, ultimately enhancing time-to-market and responsiveness to customer needs and market fluctuations.
  • Uniformity and Dependability: By formalizing infrastructure configurations and workflows, automation fosters uniformity across all environments, from development to production. This standardization mitigates the risks associated with configuration discrepancies and human errors, thus ensuring more dependable and predictable outcomes.
  • Scalability and Adaptability: Automated infrastructure provisioning equips organizations with the flexibility to dynamically scale resources up or down in response to varying demands. This elasticity enables systems to manage surges in traffic or workloads efficiently, optimizing resource allocation and reducing expenses.
  • Improved Efficiency: Automating the management and configuration of infrastructure eliminates repetitive and time-consuming manual tasks. This allows teams to allocate their time and resources to more strategic and high-value activities like innovation, problem-solving, and improving the overall customer experience.

Enabling CI/CD: Infrastructure automation is essential for facilitating Continuous Integration and Continuous Deployment (CI/CD) pipelines. It automates the deployment and testing of software changes across multiple environments, streamlining the delivery process. This results in organizations being able to release software updates more frequently, reliably, and with less risk.

How Does DevOps Infrastructure Automation Work?

Having covered the basics of DevOps Infrastructure Automation, let's explore the practices that will make the process successful.

1. Infrastructure As Code

Infrastructure as Code (IaC) transforms how organizations handle and implement their infrastructure by treating configurations as software code. This method abstracts infrastructure settings from physical hardware and represents them in scripts or configuration files. Often based on predefined rules or playbooks, these scripts enable teams to automate infrastructure resource provisioning, setup, and supervision.

The strength of IaC lies in its ability to be replicated and ensure consistency. By packaging infrastructure configurations in code, teams can apply the same scripts across various environments, guaranteeing uniformity and predictability in their infrastructure deployments. This strategy reduces the chance of errors and divergences in settings, resulting in a more dependable and effective deployment process.

Furthermore, Infrastructure as Code (IaC) improves security by addressing misconfiguration risks. Organizations can consistently implement standardized security measures across their infrastructure by utilizing predefined configurations in scripts. This proactive approach reduces the chance of security breaches and helps companies adhere to regulatory mandates, strengthening their cybersecurity defenses.

Moreover, the scalability and flexibility provided by IaC streamline the software development life cycle (SDLC). Deploying multiple systems simultaneously eliminates bottlenecks and speeds up development and delivery processes. This flexibility allows organizations to quickly adapt to changing business needs and market trends, encouraging innovation and competitiveness.

2. Continuous Integration/Continous Delivery

CI/CD is a collection of practices and principles designed to automate the software development lifecycle for quick and dependable application delivery. In DevOps, CI/CD is a core component for optimizing the building, testing, and deployment of software changes, fostering teamwork between development, operations, and other interdisciplinary teams. Let us look at how CI/CD works and what its role is in DevOps infrastructure automation.

Continuous Integration (CI): It involves automating the integration of code changes into a shared repository multiple times daily. Developers regularly commit code changes to the repository, initiating automated build and test processes.

CI pipelines validate code changes through automated tests, such as unit tests, integration tests, and code quality checks. If the tests pass successfully, the changes are considered "integrative."

By automating the integration and testing of code changes, CI helps identify and address issues early in the development process, reducing the risk of integration conflicts and ensuring code quality.

Continuous Delivery (CD): CD builds upon CI by automating the process of deploying code changes to production or staging environments. This involves automating steps such as packaging, deployment, and application testing.

CD pipelines automate deployment, allowing organizations to release software updates quickly and reliably. Automated testing and validation ensure that deployments adhere to quality standards and are prepared for production use.

CD enables teams to deliver software updates to users efficiently and with minimal manual effort, allowing organizations to respond promptly to market shifts and customer feedback.

CI/CS helps enable the DevOps Infrastructure automation in the following way.

  • Enhanced Efficiency and Dependability: Automation through CI/CD pipelines streamlines repetitive tasks like code integration, testing, and deployment, reducing the chances of human error and freeing up time for more strategic work. This automated process ensures uniformity and consistency in software delivery, resulting in a more robust and predictable infrastructure.
  • Enhanced Collaboration and Communication: CI/CD encourages teamwork and communication among development, operations, and other teams by offering real-time visibility into code changes and deployments. Automated notifications and feedback mechanisms facilitate seamless communication and alignment of goals, empowering teams to collaborate effectively towards common objectives.
  • Improved Scalability and Adaptability: CI/CD pipelines provide a flexible and scalable framework that can easily be tailored to meet evolving business demands and infrastructure requirements. Organizations can effortlessly incorporate new tests, environments, or deployment targets into their pipelines, allowing them to adjust and expand their software delivery processes as needed.
  • Improved Quality Assurance: Integrating automated testing within CI/CD pipelines guarantees that code changes adhere to quality standards before deployment. This ongoing verification process minimizes the likelihood of bugs and defects appearing in production, ultimately boosting software quality and enhancing user satisfaction.

3. Containers and Orchestration

Containers are a lightweight virtualization that consolidates applications and their dependencies into separate units, enabling them to operate consistently across various environments. All the components for an application to function are encompassed within containers, encompassing code, runtime, system tools, libraries, and configurations, guaranteeing consistent performance regardless of the environment.

In contrast, orchestration involves the automatic control and organization of containerized applications throughout a distributed infrastructure. Platforms dedicated to container orchestration, such as Kubernetes, Docker Swarm, and Amazon ECS, deliver tools and functionalities for deploying, scaling, managing, and monitoring containerized applications on a large scale.

When combined, containers with orchestration offer the following advantages.

  • Scalability: Orchestration platforms facilitate automated scaling of containerized applications based on demand. They can provision additional container instances or distribute workload across existing instances to handle spikes in traffic or workload, optimizing resource utilization and performance.
  • Resilience and High Availability: Orchestration platforms offer high availability and fault tolerance features, ensuring that containerized applications remain accessible and responsive even during infrastructure failures or disruptions. They support automatic container restarts, load balancing, and self-healing mechanisms, reducing downtime and promoting seamless operations.
  • Automation: Containers coupled with orchestration streamline different aspects of the software delivery lifecycle, such as deployment, scaling, monitoring, and recovery. Through infrastructure-as-code (IaC) and configuration management tools, DevOps teams can stipulate deployment pipelines and workflows, ultimately facilitating seamless automation of application deployment and management processes.
  • Resource Efficiency: Orchestration platforms enhance resource efficiency by dynamically scheduling and allocating containers based on application requirements and resource availability. They can consolidate multiple containers onto a single host or distribute containers across various hosts, maximizing resource utilization and reducing costs.

4. Automated Storage Resource Optimization

Optimizing storage resources hinges on ensuring efficient, scalable, and resilient operations in DevOps infrastructure automation. Organizations can improve performance, availability, and data security by matching storage configurations with application needs and workload features. Additionally, adequately optimized storage resources greatly simplify storage management, lowering administrative overhead and complexities and increasing operational efficiency.

Moreover, efficient storage management facilitates disaster recovery and business continuity by facilitating prompt data backups, replication, and recovery functions.

5. Reserved Instance Optimization

Reserved Instances (RIs) are a pricing model that provides users discounts in return for their long-term commitment to EC2, RDS, and other AWS services. RIs offer good rates in comparison to on-demand prices, making them a more effective way to cut down costs on cloud expenditures. This helps organizations save a good amount and stabilize workflow in the long run.

DevOps Infrastructure Automation Tools

Before we dive into different types of tools, it is important to understand that we are going to categorize the tools into the following categories

  • Tools for Automating Storage Resource Optimization
  • Infrastructure as Code (IaC)
  • Continuous integration and delivery
  • Container orchestration and image management
  • Config/Secret Management
  • Monitoring and logging

Now that we know what types of tools to look for to enhance DevOps infrastructure automation, let us take a look at one tool from each category.

Tools for Automating Storage Resource Optimization

Effective storage optimization reduces unnecessary overprovisioning costs and enables seamless dynamic scaling to meet fluctuating workload requirements.

But how does storage hold such importance?

We have suggested IaaC as one of the instrumental DevOps Infrastructure Automation practices. IaaC is one of the crucial aspects of cloud computing. Hence, it is essential that when you invest in a tool for DevOps infrastructure automation, you look for a tool that reduces cloud costs by reducing costs associated with storage usage and wastage.

Why so?

This is because storage is a significant contributor to cloud costs. Virtana's research study, "State of Hybrid Cloud Storage in January 2023," highlights the importance of storage costs in the overall expenses of utilizing cloud services. 

According to the study, 94% of participants reported increased cloud costs, with 54% noting a faster growth in storage-related expenses than other components of their bills. 

To delve deeper into the correlation between storage resources and cloud spending, we conducted an extensive independent analysis involving over 100 enterprises utilizing leading cloud providers like AWS, Azure, and GCP.

Based on our analysis, we have identified the following major findings:

Storage-related expenses comprise approximately 40% of total cloud costs, underscoring the significant impact of storage provisioning and management on financial resources.

Block storage services such as AWS EBS, Azure Managed Disk, and GCP Persistent Disks drive overall cloud expenditures. Our evaluation suggests that a closer review and optimization of these solutions are essential.

Despite the crucial role of block storage, our investigation uncovered surprisingly low disk utilization rates across various scenarios, including root volumes, application disks, and self-hosted databases. This inefficiency presents opportunities for right-sizing and optimization to minimize waste and improve cost-effectiveness.

Our study discovered numerous organizations frequently miscalculate storage growth and allocate excessive resources, leading to unnecessary expenses. Participants admitted to facing downtime incidents every quarter, underscoring the importance of harmonizing storage provisioning with actual demand to mitigate risks and manage costs effectively.

The abovementioned issues stem from organizations opting to overprovision resources rather than optimizing storage. Nevertheless, we recognize the rationale behind this deliberate approach, which includes.

  • Optimizing storage resources: Optimizing storage involves a multi-step process that requires time and dedication. It includes selecting the appropriate storage class, establishing data lifecycle management policies, and consistently monitoring and adjusting storage to meet specific needs.
    Therefore, DevOps teams must assess their current storage requirements to effectively address application needs, analyze data access patterns, and align storage resources accordingly. Proper planning and maintenance are essential for implementing cost-effective storage solutions, reducing data redundancy, and ensuring efficient data retrieval.
    Furthermore, DevOps teams must stay informed about advancements and enhancements cloud providers offer. These developments can improve storage efficiency through the utilization of new features. However, these tasks may require the team to allocate time and effort away from their primary responsibilities, potentially impacting productivity.
  • Development of Custom Tools: A custom storage optimization solution is needed to address the lack of advanced features that Cloud Service Providers (CSP) offer. However, creating a custom tool will require a significant DevOps resource investment and time commitment.
  • Challenges with CSP Tools: Relying on tools provided by CSPs can result in inefficient, time-consuming, and resource-intensive processes. Due to the manpower required, daily completion of such tasks may become unachievable.

Due to the above reasons, organizations prefer overprovisioning their storage instead of optimizing it. However, overprovisioning leads to paying bills for resources you need to use. This is because CSP charges you for the resources that are provisioned, regardless of whether they are being used. Since overprovisioning results in unused resources, you will be paying for resources that you are not using.

Hence, a crucial part of DevOps infrastructure automation is finding an automated solution that will help eliminate the problems associated with overprovisioning. This is where Lucidity, with its cloud cost automation solutions, comes into play. Lucidity brings two solutions to reduce the hidden costs associated with storage usage and wastage.

Lucidity Storage Audit

Lucidity Block Storage Auto-Scaler

Simplify Storage Auditing with Lucidity Storage Audit

The Lucidity Storage Audit tool simplifies the identification of overprovisioned and idle/unused storage resources through automation. Automating this process is essential, as relying solely on manual discovery techniques or monitoring tools has limitations. 

DevOps activities can be labor-intensive, and the associated implementation costs can be high. The increasing complexity of storage environments can render manual discovery and monitoring tools inadequate to manage storage resources effectively.

The Storage Audit solution from Lucidity offers valuable assistance in efficiently managing storage resources. By simply clicking a button and utilizing automated identification solutions, Lucidity provides insights on the following:

  • Overall Disk Spend: Gain an understanding of your current disk expenditure, determine your optimized bill, and potentially save up to 70% on storage costs.
  • Disk Wastage: Identify and address idle/unused and overprovisioned disk space to optimize usage and reduce waste.
  • Disk Downtime Risk: Proactively assess the possibility of downtime to avoid any financial or reputational consequences.

Benefits of Lucidity Storage Audit:

  • Efficient Audit Process: Lucidity Storage Audit simplifies the auditing process by automating tasks and eliminating the need for manual efforts or complex monitoring tools.
  • Thorough Analysis: Lucidity Storage Audit provides a comprehensive understanding of disk health and utilization. This tool offers valuable insights to optimize spending and prevent downtime by providing visibility into your storage environment.
  • Optimal Resource Allocation: Use Lucidity Audit to analyze storage utilization percentages and disk sizes to make informed decisions and improve resource allocation for maximum efficiency.

Lucidity Block Storage Auto-Scaler

Auto-scaling is among the most proficient AWS, Azure, and GCP cost optimization best practices. There is a growing need for a tool that can prove helpful in shrinking as well as expanding storage resources. This is because leading cloud service providers like AWS, Azure, and GCP do not offer live shrinkage of storage resources. 

This is where Auto-scaling comes into the picture. 

It is a critical tool for efficiently managing EBS/Managed Disks/Persistent Disks costs on AWS, Azure, and GCP as it adapts resources based on workload demands. This automated feature eliminates manual adjustments, ensuring resources are scaled appropriately without unnecessary provisioning or waste. 

Lucidity's Block Storage Auto-Scaler is the first of its kind in the industry. It autonomously orchestrates block storage to match evolving needs and effortlessly adjusts storage capacity to meet changing requirements, providing a feature-rich solution. Lucidity Block Storage Auto-Scaler boasts the following features:

benefits of Lucidity for block storage optimization over manuall
  • Effortless Deployment: With just three clicks, you can easily onboard the Lucidity Block Storage Auto-Scaler to transform your storage management process.
  • Storage Optimization: Instantly boost storage capacity and achieve a 70-80% utilization rate for maximum efficiency and cost-effectiveness.
  • Highly Responsive: Adapt swiftly to surges in traffic or workload by adjusting storage capacity in minutes, ensuring uninterrupted operations during peak demand.
  • Efficient Performance: The streamlined Lucidity agent consumes less than 2% of CPU and RAM, minimizing strain on instance resources.

Lucidity Block Storage Auto-Scaler offers the following benefits:

  • Effortlessly Automated Storage Adjustment: The Lucidity Block Storage Auto-Scaler provides seamless automation for expanding and shrinking storage resources, achieving efficient disk scaling in just 90 seconds. This simplifies the management of large data volumes, overcoming the restrictions of traditional block storage volumes that usually max out at around 8GB per minute (equivalent to 125MB/sec) with Standard block storage. Maintaining a robust buffer allows our Auto-Scaler to handle sudden data surges smoothly without exceeding the block storage throughput limit.
  • Achieve 70% Storage Savings: By utilizing automatic storage resource adjustment, you can significantly reduce costs, saving up to 70% by only paying for the necessary resources.

Tools For Infrastructure as Code (IaC)

Infrastructure as Code (IaC) refers to provisioning and managing infrastructure using code rather than manual procedures in cloud computing. This entails defining infrastructure components like virtual machines, networks, and storage in a declarative or imperative programming language rather than configuring them manually through interfaces like graphical user interfaces or command-line interfaces. One such IaaC tool is Terraform.

Terraform, developed by HashiCorp, is a standout vendor-independent infrastructure provisioning tool that enables users to automate the creation of a wide range of cloud services, including networks, databases, firewalls, and more. Its vendor-agnostic nature sets Terraform apart and contributes to its widespread adoption. Unlike some alternatives, Terraform is not tied to any specific cloud provider, giving users the flexibility to transition seamlessly between different platforms.

As an open-source tool, Terraform benefits from a thriving community of users and contributors, offering extensive support and a wealth of resources. Despite its power and versatility, Terraform maintains accessibility through its domain-specific language, HCL (HashiCorp Configuration Language). While mastering HCL may require a slight learning curve, its concise syntax and clear structure empower users to define and manage infrastructure configurations efficiently.

Tools For Continuous Integration

Continuous Integration (CI) is an essential practice in software development that emphasizes regularly integrating code changes into a shared repository. This method allows teams to identify and resolve integration errors early on, ensuring the reliability and high quality of the software during the development phase. Automated build processes are initiated immediately after developers commit their code, producing promptly tested builds.

Some of the continuous integration tools are:

  • Jenkins: Jenkins is a widely respected open-source automation server recognized for its exceptional ability to manage Continuous Integration and deployment pipelines. With Jenkins, teams can easily automate the processes of building, testing, and deploying applications. Its diverse range of plugins provides extraordinary flexibility, enabling users to customize their CI/CD workflows to meet their needs.
  • GitLab CI/CD: It easily integrates with the all-inclusive DevOps platform of GitLab, providing a smooth end-to-end CI/CD solution. This tool allows teams to define and run pipelines directly within their GitLab repositories, simplifying development processes and enhancing teamwork. GitLab CI/CD seamlessly integrates with GitLab's version control features, ensuring a seamless experience for teams that are already using GitLab for source code management.

Tools For Continuous Delivery

Upon achieving code integration, the next phase involves continuous deployment and delivery, which are essential procedures in contemporary software delivery processes. Let's examine some leading tools highly regarded for their excellence in continuous delivery and deployment, offering not just deployment automation but also advanced infrastructure automation:

  • Helm: Helm simplifies Kubernetes deployment by automating the creation, packaging, configuration, and deployment of applications to Kubernetes clusters. Managing Kubernetes YAML manifest files, particularly for basic deployments, can consume valuable time and introduce potential errors. With Helm, a single package can be effortlessly deployed to your Kubernetes cluster, streamlining the process and reducing complexity.
  • CodeFresh: CodeFresh is a comprehensive solution that manages the entire code pipeline from start to finish. Covering all aspects of DevOps, it oversees the process from the initial commit to deployment in production. With a robust collection of plugins, including Helm, and various renowned CI/CD tools like Jenkins, Codefresh offers extensive capabilities for seamless integration. In addition, it provides native support for Kubernetes clusters, facilitating application deployment and pipeline execution within Kubernetes environments.

Tools For Container Orchestration and Image Management

Container orchestration involves:

  • The automated management of containerized applications
  • Streamlining tasks like deployment
  • Scaling
  • Load balancing
  • Resource allocation across a cluster of container hosts

Orchestration platforms eliminate the need to manually manage individual containers, offering a centralized interface for overseeing the complete lifecycle of containerized applications.

Image management involves developing, storing, distributing, and maintaining container images that function as the architectural plans for operating containerized applications. These images effectively package the application code, dependencies, and runtime environment into a compact, transportable form, simplifying the deployment of applications uniformly across various environments.

Some of the leading container orchestration and image management tools are

  • Kubernetes: Kubernetes, known as K8s, is a widely used open-source container orchestration system. Originally developed by Google, it is now maintained by the Cloud Native Computing Foundation.
    This powerful platform automates deploying, scaling, and managing containerized applications, marking a significant milestone in cloud-native computing.
    Kubernetes is platform-agnostic, providing a standardized method for deploying and managing containers. Its versatility allows developers to create applications that can effortlessly move between different environments, guaranteeing portability, scalability, and reliability at every stage of development.
  • Nomad: Nomad is a versatile workload orchestrator designed by HashiCorp that is open-source and easy to use. It allows for seamless deployment and management of containers and non-containerized applications on various platforms, including on-premise and cloud environments, at large scales.

Tools For Config/Secret Management

Ensuring the security of configurations is vital for maintaining an intense, secure Software Development Life Cycle (SDLC). The following tools are dedicated to securely protecting environment variables and configurations:

  • Doppler: A multi-cloud SecretOps Platform, Doppler is essential for developers and security teams looking to enhance the security of their application secrets. Acting as a centralized repository for secrets and application configuration, Doppler provides robust support for various deployment environments such as Docker, serverless architectures, and all major cloud vendors. Widely embraced by developers globally, Doppler is the preferred choice for managing secrets across microservices, CI/CD pipelines, and multi-cloud deployment platforms, ensuring comprehensive security throughout the software ecosystem.
  • Vault: A leading product developed by HashiCorp, Vault is highly acclaimed for its exceptional infrastructure management capabilities, comparable to Terraform. Serving as a distinguished Secret Manager, Vault boasts an extensive range of integrations, emphasizing authentication and secure storage. This underscores HashiCorp's unwavering dedication to robust security measures.

Utilizing a key-value-based architecture, Vault ensures the secure storage of sensitive data, including tokens, passwords, certificates, and encryption keys. By leveraging Vault, organizations can enforce stringent access controls to protect vital assets while enabling seamless integration with various tools and platforms.

Tools For Reserve Instance Optimization

ProsperOps is one of the robust Reserve Instance optimization tool and it leverages AI-powered Reserved Instance algorithms, techniques, and AWS discount instruments to automate lifecycle management for EC2 commitments. 

It continuously scans your reservations and usage, and programmatically maintains an optimal Reserved Instances and Saving Plans portfolio.

Tools For Monitoring And Logging

Discover below some of the top tools for monitoring your cloud infrastructure:

  • Grafana: Grafana is an open-source platform designed for observability and data visualization. It provides a user-friendly online dashboard that allows you to monitor your cloud services, infrastructure, and networks on all devices.
  • Datadog: Datadog is a SaaS-based analytics and monitoring tool for DevOps teams. It enables teams to track performance metrics and monitor events for cloud-based infrastructure. Similar to Grafana, Datadog also offers support for Kubernetes monitoring.

We hope our detailed blog has provided you with comprehensive insight to begin with DevOps infrastructure automation. 

If you are looking for a way to automate your block storage optimization but can’t find an adept solution, reach out to Lucidity for a demo. We will help you uncover insights you were struggling to find. Moreover, with Lucidity’s Block Storage Auto-Scaler, you can rest assured that you will never suffer from overprovisioning or underprovisioning issues.

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