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Web Application Logging and Analytics Using SolarWinds Loggly

October 11, 2018

Application logs provide a great deal of insight, such as critical errors ruining user experiences and active security attacks requiring immediate SRE or DevOps attention. Without logs, you have no idea how users interact with your application or how well it’s running. One issue for DevOps professionals is how to properly implement a full logging solution. It’s not enough to have logs; you also need a way to manage and analyze those logs to monitor application activity and performance.

Using Amazon CloudWatch Metrics with SolarWinds Loggly

October 3, 2018

Amazon CloudWatch provides metrics and log monitoring for AWS resources like elastic compute (EC2) instances, load balancers like ELB, and more. This data is important to monitor the health of your infrastructure and applications. You can use it to better plan capacity, auto-scale your instances, and even receive alerts when there are problems.

Analyzing Jenkins Metrics: Track Broken Builds, Build Time and More

September 28, 2018

Implementing continuous delivery (CD) is a challenge for organizations of all sizes. It’s not just a matter of generating more builds more often, but of automating and optimizing the release process. To know whether you’ve done CD successfully, you need to understand whether you are checking in your code frequently enough, whether builds are being delivered successfully, and whether you’re making the build and delivery process more efficient.

Get Better Azure Log Analytics with Loggly Insight

August 30, 2018

For any organization running .NET applications, Azure is probably one of the easiest cloud providers to integrate into production deployment and set up staging environments for testing. Azure can be configured directly into Visual Studio, so developers just click a button to deploy updates without someone on the team doing traditional manual file migration. With each resource group you make in Azure, you have the option of creating log files to monitor activity.

Benchmarking PHP Logging Frameworks: Which is Fastest and Most Reliable?

August 23, 2018

How do PHP logging frameworks fare when pushed to their limits? This analysis can help us decide which option is best for our PHP applications. Performance, speed, and reliability are important for logging frameworks because we want the best performance out of our application and to minimize loss of data.

Best Practices for Web App Monitoring

August 9, 2018

The architecture of modern web applications presents new challenges for monitoring their availability and performance. We will take a whirlwind tour of best practices for monitoring your services that can provide early warning signs before your next outage.

Best Practices for Logging in Docker Swarm

June 18, 2018

What happens when you start deploying dozens, hundreds, or thousands of containers across different machines? In this post, we’ll explore the best practices for logging applications deployed using Docker Swarm.

Recreating (and preventing) last week’s AWS Availability Zone outage using Kubernetes

June 6, 2018

Last Friday, a single availability zone (AZ) in AWS began experiencing connectivity issues. In this article, we’ll describe how an AWS outage can affect your services and best practices to survive an outage without it affecting your customers.

New automated parsing for Windows, Heroku, Python, and MongoDB

December 7, 2017

We’re proud to announce our new automated parsing for logs coming from Windows, Heroku, MongoDB, and Python. Our mission is to understand the logs you are sending so we can help you find and fix problems faster. That’s why we automatically parse more types of logs than any other log management solution.

8 Handy Tips to Consider When Logging in JSON

January 4, 2017

Logging in JSON transforms your logs from raw text lines to a database of fields you can search, filter, and analyze. This gives you way more power than you would get with only raw logs. Here are some tips and choices to consider when implementing logging in JSON. It’s

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