Operations | Monitoring | ITSM | DevOps | Cloud

Whether you’re a developer debugging an application or on the DevOps team monitoring applications across several production clusters, logs are the lifeblood of the IT organization. And if you run on top of Google Kubernetes Engine (GKE), you can use Cloud Logging, one of the many services integrated into GKE, to find that useful information. Cloud Logging, and its companion tool Cloud Monitoring, are full featured products that are both deeply integrated into GKE.

When applications are deployed in the production environment, developers expect them to work smoothly without any performance issues. However, applications often experience unexpected bottlenecks, making it crucial to monitor applications. One of the simplest ways to monitor a C# application is to emit, save, and index log data for search, analysis, and troubleshooting. We’ll discuss how you can monitor your applications while making the most of C# logging.

Earlier this year Python 2 entered End of Life — and Splunk has already released versions of Splunk Cloud and Splunk Enterprise that provide a Python 3 runtime. As the developer of an app that is published to Splunkbase, if your app contains Python code, you need to update it to work with Python 3 and Splunk Enterprise 8.0 by July 1, 2020 as the Splunk Enterprise and Splunk Cloud releases after that date will no longer support the Python 2 runtime.

Even with tough economic times, e-commerce is up 25% since the beginning of March. But, fraud has increased as well; according to Malwarebytes online credit card skimming has increased by 26% in March alone. In our April “Staff Picks for Splunk Security Reading” blog post, I referenced a story about an e-commerce site getting hacked with a “virtual card skimmer” (thanks Matthew Joseff for sharing this with me).

Out of the box monitoring solutions are getting more and more difficult to implement. In addition, they may not have the features you need, and they’re always becoming more expensive. It’s no wonder you’re trying to create a cost-effective solution via infrastructure monitoring cost management on your own by using a combination of your on-site development talent and a few open-source libraries.

Platforms like Heroku give you the freedom to focus on building great applications rather than getting lost setting up and maintaining infrastructure. One of the many great features of working with it is the Heroku logs that enable monitoring your stack error troubleshooting. It helps speed up the process when things go wrong. In this Heroku tutorial, we’ll uncover best practices for making the most of Heroku logs.

Logs are an invaluable source of information, as they provide insights into the severity and possible root causes of problems in your system. But it can be hard to get the right level of visibility from your logs while keeping costs to a minimum. Systems that process large volumes of logs consume more resources and therefore make up a higher percentage of your overall monitoring budget. Further, log throughput can be highly variable, creating unexpected resource usage and financial costs.

We’ve heard from our customers that you need visibility into metrics and logs from Google Cloud, other clouds, and on-prem in one place. Google Cloud has partnered with Blue Medora to bring you a single solution to save time and money in managing your logs in a single place. Google Cloud’s operations management suite gives you the same scalable core platform that powers all internal and Google Cloud observability.