Log Analytics in Cloud Logging is now GA

Log Analytics in Cloud Logging is now GA

Log Analytics in Cloud Logging is now GA

Solving big problems usually takes a combination of the right people and the right tools. SRE, DevOps, and IT operations teams in organizations both big and small have used Google Cloud’s built-in logging service, Cloud Logging, to troubleshoot faster, recognize trends easier, and scale operations more effectively. Additionally, customers have been building homegrown solutions that combine the powers of BigQuery and Cloud Logging to help them address operational and security challenges at massive scale. Last year we introduced Log Analytics, powered by BigQuery, so more customers can bring logs and advanced analysis together without having to build the connection themselves.  

Today, we are announcing the general availability of Cloud Logging’s Log Analytics (powered by BigQuery), a capability that allows you to search, aggregate and transform all log data types including application, network and audit log data at no additional cost for existing Cloud Logging customers. We are also launching three new Log Analytics capabilities. 

Multi-region support for US and EU region

Improved query experience to save and share queries

Support for custom retention up to 10 years

To get started, upgrade your existing log buckets to Log Analytics supported buckets. 

Same logs, same cost, more value with Log Analytics 

Log Analytics brings entirely new capabilities to search, aggregate, or transform logs at query time directly into Cloud Logging with a new user experience that’s optimized for analyzing logs data. 

Centralized logging –  By collecting and centrally storing the log data in a dedicated Log Bucket, it allows multiple stakeholders to manipulate their data from the same datasource. You don’t need to make duplicate copies of the data.

Reduced cost and complexity – Log Analytics allows reuse of data across the organization, effectively saving cost and reducing complexities. 

Ad hoc log analysis – It allows for ad-hoc query-time log analysis without requiring complex pre-processing. 

Scalable platform – Log Analytics can scale for observability using the serverless BQ platform and perform aggregation at petabyte scale efficiently

By leveraging BigQuery, Log Analytics breaks down data silos helping security, networking, developer and even business teams collaborate using a single copy of data. 

New features in this release

1. Multi-region support for Log Analytics buckets 

In addition to GA, we are also announcing multi-region support for Log Analytics with log buckets in the US and EU. These new multi-regions are available for log buckets that use Log Analytics and for those that don’t.  This means that you can now store and analyze your logs in the region that is most convenient for you, improving performance and reducing latency. 

2. Improved query experience

We are also improving the query experience by allowing users to save, share and re-use recent queries. This means that you can easily reuse and share your most important queries, saving time and making it easier to get the insights you need from your logs.

Log Analytics feature: Save & Share Query

3. Retain logs up to 10 years in a Log Analytics bucket

We are rolling out the ability to support custom log retention. You can now store logs in the Log Analytics supported bucket for beyond 30 days. Standard custom log retention pricingwill apply. 

Get started today

Now that Log Analytics is Generally Available, you can upgrade your log buckets to use Log Analytics and know that it’s covered under the Cloud Logging SLA. Upgrade your log bucket today to start taking advantage of Log Analytics. 

If this is the first time you’re hearing about Log Analytics, we’ve got you covered with some materials to get you up to speed. Take a look at our blog the top 10 reasons to get started with Log Analytics, watch a recent on-demand information session we did aimed at developers, and learn more about the overall challenges we’re helping you solve in this video: Streamline software development with better insights and diagnostics.

Source : Data Analytics Read More