OpenTelemetry is not just an observability platform, it's a set of best practices and standards that can be integrated into platform engineering or DevOps.
Hydrolix is a streaming data lake platform designed to handle large amounts of immutable log data at a lower cost than traditional solutions. The platform is particularly well-suited for observability data and offers real-time query performance on terabyte-scale data. Hydrolix uses an ANSI-compliant SQL interface, is schema-based and fully indexed, and is designed for high-cardinality data. It is purpose-built for log data and focuses on data that comes in once and never changes. Hydrolix is currently used by companies in industries like media, gaming, ad tech, and telecom security that require long-term retention of data. The company recently announced a $35 million Series B round, and its technology serves as the basis for Akamai's observability product TrafficPeak. The platform is designed to save costs for companies dealing with billions of transactions a day and terabytes of data, as it can store data for longer periods than traditional solutions like Splunk or Datadog, thereby reducing costs or increasing retention.
With the addition of profiling to OpenTelemetry, we expect continuous production profiling to hit the mainstream.
This article explains the differences between observability, telemetry, and monitoring, and how they work together to help teams understand and improve their software systems. It also discusses the benefits of using OpenTelemetry, a standard for creating and collecting telemetry for software systems, and Honeycomb's observability platform.
OpenTelemetry offers a standardized process for observability, but its functionality is a work in progress. Its usefulness depends on the observability tools and platforms used in conjunction with OpenTelemetry.
append - to append the search result of one search with another (new search with/without same number/name of fields) search.
Usually to append final result of two searches using different method to arrive to the result (which can't be merged into one search)
appendpipe - to append the search results of post process (subpipeline) of the current resultset to current result set.
Typically to add summary of the current result set.
appendcols - to append the fields of one search result with other search result. Fields are added row-wise, 1st row of first search will be merged with 1st row of 2nd search.
Value of common fields between results will be overwritten by 2nd search result values.
Typically to show comparitive analysis of two search results in same table/chart.
Usually to append final result of two searches using different method to arrive to the result (which can't be merged into one search)
appendpipe - to append the search results of post process (subpipeline) of the current resultset to current result set.
Typically to add summary of the current result set.
appendcols - to append the fields of one search result with other search result. Fields are added row-wise, 1st row of first search will be merged with 1st row of 2nd search.
Value of common fields between results will be overwritten by 2nd search result values.
Typically to show comparitive analysis of two search results in same table/chart.
