Logs are one of the most valuable assets when it comes to IT system management and monitoring. As they record every action that took place on your network, logs provide the insight you need to spot issues that might impact performance, compliance, and security. That’s why log management should be part of any monitoring infrastructure.

Log maintenance has a hidden cost. Engineers optimize their instance types, storage, networking, dependencies, and much more. However, we rarely consider the engineers themselves. A DevOps culture encourages engineers to own the solutions they build. While this increases team autonomy, it risks splitting the precious bandwidth that the team has. Automation is what makes the DevOps cycle work, and it has to cover log analysis to do a thorough job of catching issues.

Fundamentally, there are logs that will be of intrinsic value to you, and others that are less business-critical. Are you aware of the logging cost to handle, analyze and store these different types of logs? Should you really have the same approach for mission-critical logs as you do for info or telemetry logs? Differentiating your approach for different logs is challenging. If no two logs are truly the same then why should you treat them the same?

The ELK stack has become a staple of log analytics in recent years, but so too have the stories of complex maintenance and poor scalability. We’re going to discuss some of the problems with a self-hosted ELK stack and the advantages of a SaaS offering like Coralogix.

One of the most frequent questions customers ask is “how do I find this in my logs?”—often followed by a request to use regular expressions in addition to our logging query language. We’re delighted to announce that we recently added support for regular expressions to our query language — now you can search through your logs using the same powerful language selectors as you use in your tooling and software!

Microservices interact in so many ways. Load balancers, security authentication, and service discovery are just the tip of the iceberg. It can get confusing, if not outright messy. But why be messy when you can be meshy? This is where service meshes come into play, linking the roles these tools have in a common ‘net’ that ties and weaves the whole architecture together. Hashicorp has produced one of the most popular of these organizational assets — Consul Connect.

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Azure Network Security Groups (NSG) are used to filter network traffic to and from resources in an Azure Virtual Network. If you’re coming from AWS-land, NSG’s combine Security Groups and NACL’s. Splunking NSG flow log data will give you access to detailed telemetry and analytics around network activity to & from your NSG's. If that doesn’t sound appealing to you yet, here are some of the many things you could Splunk with your network traffic logs from Azure.

There are so many great things that can be said about Loki – I recently wrote about them here. But today, I want to talk about something technical that has been difficult for Loki users, and how we might make it easier: using Loki for short-lived services. Historically, one of Loki’s blind spots is ingesting logs from infrastructure you don’t control, because you can’t co-locate a forwarding agent like promtail with your application logs.

Splunk is happy to announce that we now have a Hashicorp verified Terraform Provider for Splunk. The provider is publicly available in the Terraform Registry and can be used by referencing it in your Terraform configuration file and simply executing terraform init. If you're new to Terraform and Providers, the latest version of Terraform is available here. You will need to download the appropriate binaries and have Terraform installed before using the provider.