Running a truly effective software delivery pipeline means using your best tools and practices throughout the entire development lifecycle. As you shorten your software lifecycle and move toward continuous delivery, you and your team need to find opportunities to work in parallel and remove bottlenecks. One of the most significant strides you can make is achieving consistency in your software build, package, and test processes and then applying that knowledge to your production environment. Doing so will not only make you more efficient but also will give you a leg up in troubleshooting your production systems after you go live. Logging in software development and testing is one of the best ways to achieve this consistency and learn and improve the overall delivery process.

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Logging in software development and testing means both following a consistent logging framework during application or service development, and then using those logs during testing and QA to troubleshoot software issues before you deploy code into production. For companies like yours, rapid software delivery pipelines are either the norm or the desired state, so you and your team are focused on working in parallel and removing bottlenecks that can slow down your software development and deployment lifecycle. Whether you slice your monolithic applications into discrete microservices or build new applications and deliver them using containers or in a serverless architecture, automation and consistency are your best friends.

By turning your software into loosely-coupled services, you have created more freedom for your deployment cadence. This in turn frees your engineers to release each service on the timeline that makes sense for the business; some will be released once a week, others multiple times per day, and yet others according to their individual requirements. The volume of services, the addition of orchestration tools, and the varying release cadences are enough to worry any software development leader. Introducing automation and consistency in your software build, package, and testing processes is one of the best things you can do.

Use Cases

Find bugs in dev and test

  • Get rapid feedback during development
  • See software errors and failures during test
  • Identify code error causes and dependencies

Inform your logging strategy

  • Assess the efficacy of logs during dev and test
  • Rewrite logs so they’re more effective
  • Shortcut troubleshooting during production

Make developers accountable

  • Push fewer software bugs into production
  • Make developers aware of errors
  • Facilitate developer troubleshooting

Logging in software development and testing can help you speed up your software delivery pipeline and make it more continuous. Maintaining a rapid delivery cadence becomes a forcing function for your team to log consistently. Your team needs to create automated tests that rely on your logs so that you find buggy code before it goes into production and use test outcomes to learn how effective your logs are. With these insights, engineers can refine logs to be more informative and helpful during the intensity of monitoring in production.

Good logging in dev and test also contributes to developer accountability. As you decentralize your software development and delivery, it’s easy to lose track of who is doing what at any given moment. It’s equally hard to determine the root cause of software issues, especially when your team is moving quickly. If your engineers begin logging early in their dev cycles, monitoring exceptions during unit and system tests, and using logs to understand root cause and trace the flow of software execution, they are far more likely to fix problems before software is released. At the very least, this discipline will help your team shortcut the troubleshooting process by knowing where to look once code is in production.

No matter where you are on your architecture journey, how decentralized your engineering team, or how rapid or even inconsistent your software delivery cadence, Scalyr helps you do logging in development and testing the right way.

We start by centralizing and organizing your logs and making it easy to tag and identify them by their stage in the software delivery cycle, whether development, testing, or production. We also help you see those logs in context, so you can find which resources or user behavior contributed to a software exception. We identify which systems are affected by the issue. From there, we help your team members move at the pace they need because they can troubleshoot across large data sets with no performance penalty. Our customers tell us that they can search their logs orders of magnitude faster than they could via their traditional tools. When your team can move this fast, they free up their time to develop new functionality, explore issues proactively, and find and fix bugs before they get pushed into production. Finally, because all of your engineers can use Scalyr concurrently with no performance penalty, usage throttling, or extra cost, they can get ahead of software issues during the dev and test cycle, troubleshoot more efficiently during production, and become more accountable to your application’s overall success.

Why Scalyr


Go fast. Blazing-fast. Ingest logs and alert on them in real time. Perform split-second searches and visualizations, across your entire environment.

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Skip the learning curve. Point and click to search, pivot or visualize your data.  No query language expertise required.

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Using our time-series database and massive compute capacity, Scalyr will easily scale with your systems.  You also won’t break the bank as you grow with us.

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“One of the things I really value in Scalyr is the responsiveness. I can give it a really terrible-looking query with a bunch of regular expressions, and somehow it still comes back in under a second.”

Elena Tatarchenko, Senior Engineering Manager, Oracle

“We push many hundreds of gigabytes of logs to Scalyr, and I need to search back a few days sometimes, a month even. The fact that I can still do that is just great.”

Jeff Watts, Senior Engineering Manager, Periscope Data

“Asking how Scalyr helps is like asking how breathing helps with your life.”

Tim Kröger, Head of Engineering, Zalando

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