Optimized data for Software Developers
Eliminate Firefighting
Accelerate Resolution Times
Improve observability by boosting the "signal to noise ratio" of your telemetry data and directing it to the appropriate team. Aligning data formats across platforms enhances interoperability and root cause identification, while data enrichment deepens problem comprehension. With a collaborative team armed with superior data, issue resolution becomes more effective.
Benefit
01
Get Deeper Insights
Identify specific values, such as response time, to create metrics. Mezmo's Events to Metrics Processor provides an easy way to create a new metric event within the pipeline, typically from an existing log message. The new metric event can use data from the log to generate the metric, including the desired value.
Benefit
02
Increase Data Utility
Mezmo Telemetry Pipeline expands the usability of your telemetry data. Pipeline gets it in the right format, routes it to every team that needs it, and integrates it with your current analytics tools. Data enrichment adds additional context for easier troubleshooting. This boosts your team's ability to efficiently manage application performance, service reliability, and security, leading to increased effectiveness across the board.
Benefit
03
WHAT IS Mezmo TELEMETRY PIPELINE
MEZMO TELEMETRY PIPELINE
Mezmo helps you confidently harness value from your telemetry data. Using Understand, Optimize, and Respond approach, Mezmo Flow leverages AI capabilities to analyze telemetry data sources, identify noisy log patterns, and create a data-optimizing pipeline with a few simple clicks, that routes data to any observability platform to dramatically cut log volumes and improve data quality. When you have an incident, get an in-stream alert or automatically react using Mezmo’s responsive pipelines in incident mode to get you the telemetry data you need to accelerate time to resolution.
Control Data
Control data volume and costs by in as little as 15 minutes by using Mezmo Flow. Mezmo Flow will help with identifying unstructured telemetry data, removing low-value and repetitive data, and using sampling to reduce chatter. Employ intelligent routing rules to send certain data types to low-cost storage.
- Filter: Use the Filter Processor to drop events that may not be meaningful or to reduce the total amount of data forwarded to a subsequent processor or destination.
- Reduce: Take multiple log input events and combine them into a single event based on specified criteria. Use Reduce to combine many events into one over a specified window of time.
- Sample: Send only the events required to understand the data.
- Dedupe: Reduce “chatter” in logs. The overlap of data across fields is the key to having the Dedup Processor work effectively. This processor will emit the first matching record of the set of records that are being compared.
- Route: Intelligently route data to any observability, analytics, or visualization platform.
Transform Data
Increase your data value and quality by transforming and enriching data. Reformat data as needed for compatibility with various end destinations. Scrub sensitive data, or encrypt it to maintain compliance standards.
- Parse: Various parsing options available to create multiple operations such as convert string to integers or parse timestamps.
- Aggregate Metrics: Metric data can have more data points than needed to understand the behavior of a system. Remove excess metrics to reduce storage without sacrificing value.
- Encrypt: Use the Encrypt Processor when sending sensitive log data to storage, for example, when retaining log data containing account names and passwords.
- Event to Metric: Create a new metric within the pipeline from existing events and log messages.
Deliver Insights
With Mezmo you can extract insights before the data reaches high-cost destinations. You can monitor the health of your data pipeline and run various tests before you deploy your solution.
- Monitor the health of pipelines with OOB dashboards.
- Derive metric data from Logs by parsing the log data to extract specific information.
- Count specific events within the log data and use that count to create a metric.
- Use simulation to test your pipelines before you deploy
- Send to Mezmo Log Management for analysis and insights
