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SignalFlows to SLOs

How are you tracking the long-term operation and health indicators for your micro and macro services? Service Level Indicators (SLIs) and Service Level Objectives (SLOs) are prized (but sometimes “aspirational”) metrics for DevOps teams and ITOps analysts. Today we’ll see how we can leverage SignalFlow to put some SLOs Error Budget tracking together (or easily spin up same with Terraform)!

New Features in the Content Pack for Monitoring and Alerting

The 1.7 release of the Splunk App for Content Packs comes with a slew of new awesomeness for the Content Pack for ITSI Monitoring and Alerting designed to bolster your IT operations team’s visibility and AIOps posture! Previous versions of the content pack focused on making it easy for you to create and group Notable Events from ITSI Services and third-party monitoring tools.

Dashboard Design: Getting Started With Best Practices (Part 1)

Every day, dashboards are viewed more than 500,000 times at Splunk. They’re what make the sea of data intelligible and help tell a story when working with a team. However, constant net-new dashboard creation is not necessarily a value-add activity — it’s a workflow to rapidly turn data into doing.

Splunk APM Expands Code Profiling Capabilities with Several New GAs

We’re excited to share new Splunk capabilities to help measure how code performance impacts your services. Splunk APM’s AlwaysOn Profiling now supports.NET and Node.js applications for CPU profiling, and Java applications for memory profiling. AlwaysOn Profiling gives app developers and service owners code level visibility into resource bottlenecks by continuously profiling service performance, at minimal overhead.

Using Splunk Observability Cloud to Monitor Splunk RUM

As a principal engineer on the Splunk Real User Monitoring (RUM) team who is responsible for measuring and monitoring our service-level agreements (SLAs) and service-level objectives (SLOs), I depend on observability to measure, visualize and troubleshoot our services. Our key SLA is to guarantee that our services are available and accessible 99.9% of the time.

Snowflake DB: Observing a Snowflake From Cloud to Chart

You’ve probably heard something like this before: “It’s a managed service! We don’t need to worry about anything!” But when it comes to your production workloads, database monitoring is imperative. With the new Snowflake Dashboards and Detectors in the Splunk Observability Content Contributors repository you can start seeing the details of individual Snowflakes.

IT Salaries: Trends, Roles, & Locations for 2022-2023

IT roles have never been more in demand and IT salaries have never been higher, according to recent reports and data sources. Whether you are hiring, looking for a career change, or simply work in tech, it’s important to stay up-to-date on the state of employment in the industry. This blog post will review, roundup, and summarize some of the latest trends for IT salaries and demand by role and location (among other variables) to help you get a clear view of the landscape.

How Cloud Network Monitoring Is Critical To Business Success

A rising number of businesses are adopting and utilizing cloud services and capabilities with remarkable success. But embracing cloud tools and services often brings unexpected changes for business leaders and IT teams, especially because of the way in which cloud adoption has altered how networks are monitored and managed.

To Observability and Back Again: A Context's Journey

How do you pass context from events that concern Security teams to Development teams who can make changes and address those events? Often this involves a series of meetings and discussion that can take days or weeks to filter down from security event to developer awareness. Compounding the problem, developers generally do not have access to Splunk Core, Cloud or Enterprise indexes used by security teams, and indeed, may use only Splunk Observability for their metrics, traces and even logs.

Data Observability Explained: How Observability Improves Data Workflows

Organizations in every industry are becoming increasingly dependent upon data to drive more efficient business processes and a better user experience. As the data collection and preparation processes that support these initiatives grow more complex, the likelihood of failures, performance bottlenecks, and quality issues within data workflows also increases.