As enterprises adopt cloud-based technologies, their IT infrastructure becomes more complex. The need to constantly scale up the CI/CD pipeline presents new challenges for IT teams.
This blog post will share best practices and learnings from our work with enterprise customers who have successfully scaled up their CI/CD pipelines and discuss how to solve these challenges with Cloudify in production environments.
Complexities of Enterprise IT Infrastructure
In the past, enterprise IT infrastructure was pretty simple. A few servers, some storage, and a network switch or two were all you needed to run most applications. Today, that’s no longer the case. Modern business applications are complex and require much more than hardware to run smoothly.
The complexity of your environment isn’t just limited to technology; there are challenges on the human side as well. As your organization grows, so does the number of people working within it. And with each new employee comes an increased risk for error and downtime if they don’t understand what they’re doing in their day-to-day jobs.
Cloud-based Technologies and the Increased Challenges for ITOps
As organizations have adopted cloud-based technologies, IT operations teams have also seen an increase in data. This massive amount of data presents new challenges for IT operations teams. The increased number of changes being made to the infrastructure makes it hard to keep track of them all.
Many manual tasks are required to ensure that the architecture follows best practices, which can be time-consuming and inefficient.
The Need for Scaling
As a growing organization, you might face the problem of scaling up your CI/CD pipeline management as the number of teams, features, and environments increases. Suppose in your AWS internal environment you have ~50 static assets and ~600 – 800 instances going up and down daily for QA/ development purposes (mostly spot). You need to understand how to scale up your process and make it more efficient by applying best practices.
There is the need to deploy multi-cloud and hybrid cloud CI CD integration to test the shift from manual requests to automatic provisioning. A few steps can help you in improving your CI/CD process:
- Understand what needs to be automated to achieve faster time to market, quicker code releases, and greater visibility into the quality of code produced.
- Identify all steps involved in building and deploying an application from the source code repository.
- Build scripts (if any), manual tasks, or manual approvals along with service level agreements (SLAs) for each step which should be automated.
Why is Enterprise Infrastructure Complex?
The complexity of enterprise infrastructure can make it difficult for IT teams to adopt cloud-based technologies, such as CI/CD pipelines.
Enterprise-level infrastructure is made up of many different components. These components may be located in separate physical locations or in various organizations. The complexity of managing this infrastructure makes it challenging to adopt new technologies specifically if your organization is growing and needs a more robust pipeline management solution.
Why are there so many moving parts? Because companies want the flexibility to run their applications where they see fit, from their private data center(s) or using public cloud providers like AWS and Google Cloud Platform (GCP).
This means that most companies have multiple environments where their applications might be running. When you combine those with the number of teams responsible for managing them and ensuring policies stay up-to-date, you’ve got quite a few things that need automation tools applied.
Why should you Scale Up Your Pipeline as Your Organization Grows?
Let’s say you have one application and one environment with two teams working on them. The next year, two additional applications were added, and each team was assigned an additional environment (or branch). This would mean that there are now four environments being used by four teams—a major increase in the number of applications and branches!
A second example is when more users are added than before: if only 10 people were using the system last year, but now 50 new ones are coming into play, it may require an upgrade of resources or configuration changes to accommodate everyone effectively.
Therefore, the challenges you face are as follows:
Pipelines have to be dynamic
When you are working on a CI CD pipeline and scaling it, you will need to make sure that your pipeline is flexible and can accommodate changes. As the product evolves, so does the pipeline. This may mean that you have to keep adding new stages or even re-arrange existing ones.
Pipeline needs to have adaptability for growth
If you’re building microservices and your software is going through a period of rapid growth, then it’s likely that your CI CD pipeline will need to scale up with them. This can mean adding more nodes or capacity, but also making sure that your pipeline has the ability to run in parallel across multiple machines or containers.
Ability to scale with the release of new product features
The ability for a pipeline to scale up and down as needed can be crucial for a business that wants to keep costs under control while also maintaining a competitive edge in terms of speed and agility. Being able to grow with demand is important for any organization looking to expand its operations and increase revenue streams.
Automation leads to efficient application scaling
How do you improve now that you have a CI/CD pipeline? Here are some best practices to consider:
- Streamline your tests before a CI/CD pipeline deployment: Once your team has been using the CI/CD pipeline for a while, it’s essential to revisit the test suite and see if there are any unnecessary tests. Are some tests duplicated? Do they run too long? These are all things that can be improved as your team grows.
- Do not bypass your CI/CD pipeline: When code is committed and integrated into the master, it must go through the same process as other changes (code reviews, unit testing) before being released into production—this ensures quality control throughout all development stages.
- Monitor and measure performance of each step: Make improvements over time by identifying bottlenecks or areas where certain tasks take longer than they should (and fixing them!). This will help prevent bugs from slipping through later on downstream when more people have access to release branches like QA or production environments.
How can you Measure Success in CI/CD Scale-ups?
With a mature CI CD pipeline deployment strategy, you can measure success in several ways. The most important measure is lead time. As your team grows, it will take longer and longer to get changes through the pipeline. This will be due to the increased complexity of your codebase, which makes testing more challenging.
For example, if your team requires two weeks to get code from commit to production, this could be considered a failure. If it takes three months, however, then it’s probably not that big of an issue.
The second is the deployment frequency. How many times per day/ week/ month do you deploy CI/CD? If your pipeline has grown too long, you may find that it takes over an hour or two between each deployment step and if this problem goes on long enough. If you don’t fix it early enough in its life cycle (before it becomes too big), you might have trouble making frequent deployments even when everyone knows they should be doing so.
Another measure of success is mean time to recovery (MTTR). How long does it take to fix a production issue caused by a broken build or deployment? No one wants their MTTR to go up as their CI/CD pipeline scales; however, quality assurance improvements can sometimes cause increases without any related increase in MTBF (mean time between failures).
And lastly, we have a change failure rate. This measures how often builds fail after being submitted by developers. If these numbers start going up significantly as well, this could indicate that something needs improving before things start going downhill fast!
Benefits of Using Best Practices for Scaling Up CI/CD
Using best practices for scaling up CI/CD can have several benefits, including:
- Improving your pipeline. A well-maintained pipeline will allow you to move faster and reduce costs by avoiding manual work.
- Increasing speed. A consistent process run on a large amount of data will be quicker than one run on small sets, as the former takes advantage of economies of scale that are otherwise unavailable with smaller sets.
- Reducing costs. Large datasets are distributed across multiple sites to complete analysis tasks quickly, making it possible for more people within an organization to use them simultaneously without incurring excessive costs due to equipment needs.
How can you do it with Cloudify?
Cloudify is a DevOps automation and environment management platform for deploying and managing containerized applications across multi-cloud and hybrid-cloud environments.
Cloudify is designed to manage stateless and stateful applications, focusing on Kubernetes and Docker containers.
By offering built-in scheduling, delivery pipelines (via Blue/Green deployments), monitoring, logging, tracing, and governance functionalities, Cloudify provides a single solution to unify your cloud management needs across the entire software development lifecycle.
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