Operations | Monitoring | ITSM | DevOps | Cloud

Organizations and their software delivery pipelines are continually exposed to growing cyberattack vectors. Coupled with the massive adoption of open source software, which now helps power nearly all of our public infrastructure and is highly prevalent in most proprietary software, businesses around the world are more vulnerable than ever. Today’s organizations need to be more vigilant in protecting their software development infrastructure and processes.

As Kubernetes monitoring continues to standardize on Prometheus as a form factor, more and more developers are becoming familiar with Prometheus’ built-in query language, PromQL. Besides being bundled with Prometheus, PromQL is popular for being a simple yet expressive language for querying time series data. It’s been fully adopted by the community, with lots of great query repositories, sample playbooks, and trainings for PromQL available online.

Logging is a critical part of the software development lifecycle allowing developers to debug their apps, DevOps/SRE teams to troubleshoot issues, and security admins to analyze access. Cloud Logging provides a powerful pipeline to reliably ingest logs at scale and quickly find your logs. Today, we’re pleased to announce Log Analytics, a new set of features in Cloud Logging available in Preview, powered by BigQuery that allows you to gain even more insights and value from your logs.

GitOps takes DevOps best practices used for application development (such as version control and CI/CD) and applies them to infrastructure automation. In GitOps, the Git repository serves as the source of truth and the CD pipeline is responsible for building, testing, and deploying the application code and the underlying infrastructure. Nowadays, an application is not just code running on infrastructure that you own and operate.

An essential aspect of operating any application is the ability to observe the health and performance of that application and of the underlying infrastructure to quickly resolve issues as they arise. Google Kubernetes Engine (GKE) already provides audit logs, operational logs, and metrics along with out-of-the-box dashboards and automatic error reporting to facilitate running reliable applications at scale.

Does your development team want to snooze alerts during non-business hours? Or proactively prevent the creation of expected alerts for an upcoming expected maintenance window? Cloud Alerting in Google's Cloud operations suite now supports the ability to snooze alert policies for a given period of time. You can create a Snooze by providing specific alert policies and a time period. During this window, if the alert policy is violated, no incidents or notifications are created.

Many organizations struggle to create data-driven cultures where each employee is empowered to make decisions based on data. This is especially true for enterprises with a variety of systems and tools in use across different teams. If you are a leader, manager, or executive focused on how your team can leverage Google's SRE practices or wider DevOps practices, definitely you are in the right place!

The new version of the Google logging client library for Go has been released. Version 1.5 adds new features and bug fixes including new structured logging capabilities that complete last year's effort to enrich structured logging support in Google logging client libraries. Here are few of the new features in v1.5: Let's look into each closer.

According to a recent CNCF survey, 86% of the cloud native community reports that they use Prometheus for observability. As Prometheus becomes more of a standard, an increasing number of developers are becoming fluent in PromQL, Prometheus’ built-in query language. While it is a powerful, flexible, and expressive query language, PromQL is typically only able to query Prometheus time series data.

We’re thrilled to announce the release of a new update to the Cloud Logging Library for Node.js with the key new features of improved error handling and writing structured logging to standard output which becomes handy if you run applications in serverless environments like Google Functions!