Operations | Monitoring | ITSM | DevOps | Cloud

Ask any DevOps engineer, and they will tell you about all the alerts they enable so they can stay informed about their code. These alerts are the first line of defense in the fight for Perfect Uptime SLA. With every good solution out there, you can find plenty of methods for alerting and monitoring events in the code. Each method has its own reasons and logic for how it works and why it’s the best option. But what can you do when you need to connect two opposing methodologies? You innovate!

At Payoneer, we use Coralogix to collect logs from all our environments from QA to PROD. Each environment has its own account in Coralogix and thus its own limit. Coralogix price modules are calculated per account. We as a company have our budget per account and we know how much we pay per each one. In case you exceed the number of logs assigned per account you will pay for the “extra” logs. You can see the exact calculation in this link.

Infrastructure as Code is an increasingly popular DevOps paradigm. IaC has the ability to abstract away the details of server provisioning. This tutorial will look at how Coralogix can be used with the popular IaC tool Terraform.

Two popular deployment architectures exist in software: the out-of-favor monolithic architecture and the newly popular microservices architecture. Monolithic architectures were quite popular in the past, with almost all companies adopting them. As time went on, the drawbacks of these systems drove companies to rework entire systems to use microservices instead.

The term ‘cloud native’ has become a much-used buzz phrase in the software industry over the last decade. But what does cloud-native mean? The Cloud Native Computing Foundation’s official definition is: From this definition, we can differentiate between cloud-native systems and monoliths which are a single service run on a continuously available server. Like Amazon’s AWS or Google Azure, large cloud providers can run serverless and cloud-native systems.

When teams begin to analyze their logs, they almost immediately run into a problem and they’ll need some JSON logging tips to overcome them. Logs are naturally unstructured. This means that if you want to visualize or analyze your logs, you are forced to deal with many potential variations. You can eliminate this problem by logging out invalid JSON and setting the foundation for log-driven observability across your applications.

Kibana is the most popular open-source analytics and visualization platform designed to offer faster and better insights into your data. It is a visual interface tool that allows you to explore, visualize, and build a dashboard over the log data massed in Elasticsearch clusters. An Elasticsearch cluster contains many moving parts. These clusters need modern authentication mechanisms and they require security controls to be configured to prevent unauthorized access.

Log observability and monitoring are terms often used interchangeably, but really they describe two approaches to solving and understanding different things. Observability refers to the ability to understand the state of a complex system (or series of systems) without needing to make any changes or deploy new code.

A Content Delivery Network (CDN) is a distributed set of servers that are designed to get your web-based content into the hands of your users as fast as possible. CDNs produce CDN logs that can be analyzed, and this information is invaluable. Why? CDNs host servers all over the world and are designed to help you scale your traffic without maxing out your load balancers. A CDN also gives you added protection against many of the most common cyber attacks. This activity needs to be closely monitored.

Observability and its implementation may look different to different people. But, underneath all the varying definitions is a single, clear concept: Most software that’s run today uses microservices or loosely coupled distributed architecture. While this design makes scaling and managing your system more straightforward, it can make troubleshooting issues more difficult. The three pillars of observability are different methods to track software systems, especially microservices.