The observability landscape is constantly changing and evolving. Despite this, one question often plagues operations leaders: "How can we consolidate disparate data sources and tools to view system performance comprehensively?" These leaders have sought the answer in a single-pane-of-glass solution. However, as Jason Bloomberg and Buddy Brewer discussed in the Mezmo webinar "Solving the Single Pane of Glass Myth," this idea is more myth than reality.

Data explosion is prevalent and impossible to ignore in today’s business landscape, with organizations face a pressing challenge: the ever-increasing volume of log data. As applications, systems, and services generate a torrent of log entries, it becomes crucial to find a way to navigate this sea of information and extract meaningful value from it. How can you turn the overwhelming volume of log data into actionable insights that drive business growth and operational excellence?

Log data is the most fundamental information unit in our XOps world. It provides a record of every important event. Modern log analysis tools help centralize these logs across all our systems. Log analytics helps engineers understand system behavior, enabling them to search for and pinpoint problems. These tools offer dashboarding capabilities and high-level metrics for system health. Additionally, they can alert us when problems arise.

Growth of cloud computing and the preference for data-driven decision-making have led to a steady increase in investments in observability over the years. Telemetry data is recognized as not only critical for maintaining a company’s infrastructure, but also for aiding security and business teams in making informed decisions. However, just increasing investment in observability technology is not enough.

In modern business environments, where everything is fast-paced and data-centric, companies need to be able to track and analyze data quickly and efficiently to stay competitive. Metrics play a crucial role in this, providing valuable insights into product performance, user behavior, and system health. By tracking metrics, companies can make data-driven decisions to improve their product and grow their business.

Mezmo Telemetry Pipeline helps organizations Ingest, transform, and route telemetry data to control costs and drive actionability. Modern organizations are adopting telemetry pipelines to manage challenges with telemetry data (logs, metrics, traces, events) growth and to get the most value from their data investments.

Grafana is a popular open-source tool for visualizing and analyzing data from various sources. It provides a platform for creating interactive, customizable dashboards that display real-time data in various formats, including graphs, tables, and alerts. When powered by Mezmo's Telemetry Pipeline, Grafana can access a wide range of data sources and provide a unified view of the performance and behavior of complex systems.

Elasticsearch has made a name for itself as a powerful, scalable, and easy-to-use search and analytics engine, enabling organizations to derive valuable insights from their data in real-time. However, to truly unlock the potential of Elasticsearch, it is essential that the right data in the right format is provisioned to Elasticsearch. This is where integrating a telemetry pipeline can add value to Elasticsearch.

With 85 of their customers listed among the Fortune 100 companies, Splunk is undoubtedly one the leading machine data platforms on the market. In addition to its core capability of consuming unstructured data, Splunk is one of the top SIEMs on the market. Splunk, however, costs a fortune to operate – and those costs will only increase as data volumes grow over the years. Due to these growing pains, technologies have emerged to control the increasing costs of using Splunk.

When it comes to handling and deriving insights from massive volumes of data, Splunk is a force to be reckoned with. Its ability to index, search, and analyze machine-generated data has made it an essential tool for organizations seeking actionable intelligence. However, as the volume and complexity of data continue to grow, optimizing the Splunk experience becomes increasingly important. This is where the power of telemetry pipelines, like Mezmo, comes into play.