# Mezmo Docs: Telemetry Pipelines > Explore guides, APIs, tutorials, and reference materials for collecting telemetry and using Mezmo’s SRE agent to manage production environments. ## Telemetry Pipelines ### About Pipelines - [About Mezmo Telemetry Pipelines](https://docs.mezmo.com/telemetry-pipelines/about-mezmo-telemetry-pipelines.md): Overview of how Mezmo Telemetry Pipelines ingest, process, route, and monitor telemetry data across diverse sources and destinations. - [Getting Started with Mezmo Telemetry Pipelines](https://docs.mezmo.com/telemetry-pipelines/getting-started-with-mezmo-telemetry-pipeline.md): Learn the core concepts of Mezmo Pipelines, including sources, processors, destinations, ingress/egress usage metrics, and how to create an account. - [Build and Deploy a Mezmo Telemetry Pipeline](https://docs.mezmo.com/telemetry-pipelines/build-deploy-mezmo-pipeline.md): Step-by-step instructions to build a Pipeline from Sources, Destinations, and Processors in the Mezmo Web App, then deploy and view it. - [View and Sample Pipeline Data](https://docs.mezmo.com/telemetry-pipelines/view-pipeline-data.md): Use a Pipeline Tap to view data streaming between nodes of a deployed Pipeline and capture samples for simulating and testing your processors. - [Monitor Pipeline Data Volume](https://docs.mezmo.com/telemetry-pipelines/monitor-data-pipelines.md): Use the Pipelines dashboard to track aggregated and per-source/destination Ingress and Egress volume, top 10 sources and destinations, and per-Pipeline metrics. - [About Mezmo Trial Accounts](https://docs.mezmo.com/telemetry-pipelines/about-mezmo-trial.md): What the free 30-day Mezmo trial includes, how to select a plan when it ends, and where to start building your first Pipeline. - [Configure Responsive Pipelines](https://docs.mezmo.com/telemetry-pipelines/configure-responsive-pipelines.md): Pre-configure Pipelines to switch between normal and incident states automatically, balancing high-fidelity data with cost reduction. - [Replay Buffered Data](https://docs.mezmo.com/telemetry-pipelines/replay-buffered-data.md): Automatically re-process recently buffered push-source data through a Responsive Pipeline when it enters incident state, so full-fidelity data is indexed into Mezmo Log Analysis. - [Shared Sources](https://docs.mezmo.com/telemetry-pipelines/shared-sources.md): Configure a source once at the global level and reuse it across multiple pipelines, transmitting the same data only once to reduce volume and management. - [Create a Data Profile](https://docs.mezmo.com/telemetry-pipelines/data-profiling.md): Use the Data Profiler to get a granular view of your log data through Message Templates, Field Summaries, and Log Metrics reports. - [About Mezmo Flow](https://docs.mezmo.com/telemetry-pipelines/about-mezmo-flow.md): Learn how Mezmo Flow profiles your telemetry data and recommends Processors to build a volume-reducing Pipeline in four steps. ### Sources - [Set Up Pipeline Sources](https://docs.mezmo.com/telemetry-pipelines/set-up-pipeline-sources.md): Create a pipeline and add a source to begin ingesting log data from one of the supported telemetry pipeline sources. - [Azure Event Hub](https://docs.mezmo.com/telemetry-pipelines/azure-event-hub-source.md): Ingest data from an Azure Event Hub into Mezmo Pipelines via the Kafka interface, including prerequisites and configuration options. - [Demo Logs](https://docs.mezmo.com/telemetry-pipelines/demo-logs-source.md): Ready-to-use demo log sources in formats like NGINX, Apache, syslog, JSON, and metrics for building and testing your Pipelines. - [FluentD and FluentBit](https://docs.mezmo.com/telemetry-pipelines/fluent-source.md): Stream FluentD and FluentBit logs and metrics to Mezmo Pipelines using HTTP output plugins for SaaS or Forward plugins for Edge. - [HTTP](https://docs.mezmo.com/telemetry-pipelines/http-source.md): Send data to a Mezmo Pipeline via a RESTful POST when a native source type isn't supported, then parse it in-stream to extract fields. - [HTTP Client](https://docs.mezmo.com/telemetry-pipelines/http-client-source.md): A pull source that polls an HTTP endpoint on a schedule and ingests the responses into your pipeline, with configurable method, interval, headers, decoding, and authentication. - [Kafka](https://docs.mezmo.com/telemetry-pipelines/kafka-source.md): A pull source that collects events from Kafka-compatible brokers, with configurable topics, consumer group, TLS, and SASL/SCRAM authentication. - [AWS Kinesis Firehose](https://docs.mezmo.com/telemetry-pipelines/kinesis-firehose-source.md): Stream near real-time data into your Mezmo Pipeline from AWS Kinesis Firehose by configuring the HTTP endpoint and API key on your delivery stream. - [Mezmo Log Analysis Ingestion](https://docs.mezmo.com/telemetry-pipelines/log-analysis-ingestion-source.md): Redirect data sent to the logs.mezmo.com Log Analysis endpoint into a Pipeline Source, supporting agent, ingest, syslog, and Heroku endpoints. - [Mezmo Log Analysis](https://docs.mezmo.com/telemetry-pipelines/log-analysis-source.md): A deprecated source that forwards logs from your Log Analysis account into a Pipeline, including the metadata query fields it attaches to each event. - [Mezmo Agent](https://docs.mezmo.com/telemetry-pipelines/mezmo-agent-source.md): Stream log data from the Mezmo Agent directly into a Pipeline, including configuration variables, migration from Log Analysis, and Helm installation. - [Datadog Agent](https://docs.mezmo.com/telemetry-pipelines/mezmo-datadog-source-source.md): Receive logs and metrics directly from the Datadog Agent over HTTPS into a Mezmo Pipeline, with setup, configuration, and Docker/host examples. - [Datadog Agent V2](https://docs.mezmo.com/telemetry-pipelines/mezmo-datadog-source-v2-source.md): Receive logs, metrics, and traces from a Datadog Agent on separate output ports so each telemetry type can be routed independently. - [OpenTelemetry Source](https://docs.mezmo.com/telemetry-pipelines/open-telemetry-source.md) - [Pipeline Data Restoration](https://docs.mezmo.com/telemetry-pipelines/pipeline-data-restoration-source.md): Source that lets you restore telemetry data from an archive location into a Pipeline, with no configuration options required. - [Logstash](https://docs.mezmo.com/telemetry-pipelines/logstash-source.md): Send data from your Logstash instance to Mezmo Pipelines using the HTTP output plugin with string or JSON formatting. - [Prometheus Remote Write](https://docs.mezmo.com/telemetry-pipelines/prometheus-remote-write-source.md): Send metrics to a Mezmo Pipeline using the Prometheus Remote Write source, with a unique endpoint URL and Bearer Token authentication. - [AWS S3 via SQS](https://docs.mezmo.com/telemetry-pipelines/s3-source.md): Use log data stored in Amazon S3 as a pipeline source via Amazon SQS to rehydrate, parse, and route archived data for analysis or compliance. - [Splunk HEC](https://docs.mezmo.com/telemetry-pipelines/splunk-hec-source.md): Use the Splunk HTTP Event Collector as a pipeline source to route, reduce, and process events before forwarding them on to Splunk or a SIEM. - [Syslog over HTTP](https://docs.mezmo.com/telemetry-pipelines/syslog-over-http-pipeline-source.md): Send Syslog events to Mezmo Pipelines through an HTTP endpoint over TLS, including an example rsyslog om-http configuration. - [AWS SQS](https://docs.mezmo.com/telemetry-pipelines/sqs-source.md): Stream log data from an Amazon SQS queue as a pipeline source, including SQS setup, the required access policy, and IAM permissions. - [Webhook (WebSub)](https://docs.mezmo.com/telemetry-pipelines/webhook-source.md): Accept RESTful webhook messages using the WebSub protocol, verifying payloads with an HMAC signature based on a configured signing key. ### Processors - [Set Up Pipeline Processors](https://docs.mezmo.com/telemetry-pipelines/set-up-pipeline-processors.md): Insert processors between a connected source and destination to reduce, reformat, or extract information from log data in your pipeline. - [Aggregate Processor](https://docs.mezmo.com/telemetry-pipelines/aggregate-processor.md): Aggregate metric and log fields over tumbling or sliding windows and trigger threshold or change alerts when conditions are met. - [Compact Fields Processor](https://docs.mezmo.com/telemetry-pipelines/compact-fields-processor.md): Recursively remove empty arrays and objects from a specified field to clean up null values and empty spaces in messages. - [Data Profiler Processor](https://docs.mezmo.com/telemetry-pipelines/data-profiler-processor.md): Analyze Source data to surface the most common message patterns and the apps and hosts driving log volume, with field mapping options. - [Decrypt Field Processor](https://docs.mezmo.com/telemetry-pipelines/decrypt-fields-processor.md): Decrypt an encrypted string field using a secret key and initialization vector, reversing the Encrypt Field Processor. - [Remove Fields Processor](https://docs.mezmo.com/telemetry-pipelines/drop-fields-processor.md): Drop specified JSON fields from each record in the data stream before sending it to storage or other processors. - [Dedupe Processor](https://docs.mezmo.com/telemetry-pipelines/dedupe-processor.md): Remove duplicate log records across a set of events using Match or Ignore comparison on specified fields to reduce log chatter. - [Encrypt Field Processor](https://docs.mezmo.com/telemetry-pipelines/encrypt-fields-processor.md): Apply an encryption algorithm and key to a specified field to protect sensitive log data before sending it to storage. - [Event to Metric Processor](https://docs.mezmo.com/telemetry-pipelines/event-to-metric-processor.md): Create a counter, sum, or gauge metric event from a log message, drawing the metric values from event fields or static values. - [Filter Processor](https://docs.mezmo.com/telemetry-pipelines/filter-processor.md): Pass or drop events using conditional statements with content, string, comparison, and type operators to reduce forwarded data. - [Flatten Fields Processor](https://docs.mezmo.com/telemetry-pipelines/flatten-fields-processor.md): Recursively collapse nested JSON objects into a single level, joining parent and child keys with a configurable delimiter. - [Script Execution Processor](https://docs.mezmo.com/telemetry-pipelines/js-script-processor.md): Transform events using a subset of JavaScript to filter, drop, map, and cast data within a single script, with supported functions and operators. - [Map Fields Processor](https://docs.mezmo.com/telemetry-pipelines/map-fields-processor.md): Move or copy fields within an event, including nested fields, with options to drop the source field or overwrite an existing target. - [Tag Cardinality Limit Processor](https://docs.mezmo.com/telemetry-pipelines/metrics-tag-cardinality-limit-processor.md): Cap the number of unique tag values per metric using exact or probabilistic matching, dropping the offending tag or the entire event when the limit is reached. - [Parse Processor](https://docs.mezmo.com/telemetry-pipelines/parse-processor.md): Convert incoming data of a known format into parsed values using parsers like CSV, Grok, JSON, Regex, and timestamps, plus AI-assisted pattern matching. - [Parse Sequentially Processor](https://docs.mezmo.com/telemetry-pipelines/parse-sequentially-processor.md): Configure multiple parsers on a single node that are tried in order, applying the first parser that matches the incoming data. - [Redact Processor](https://docs.mezmo.com/telemetry-pipelines/redact-processor.md): Identify and redact PII such as SSNs, emails, credit cards, and phone numbers in your data stream using pattern detection, hashing, or replacement. - [Reduce Processor](https://docs.mezmo.com/telemetry-pipelines/reduce-processor.md): Combine multiple log events into a single event over a time window using group-by fields and configurable per-field merge strategies. - [Route Processor](https://docs.mezmo.com/telemetry-pipelines/route-processor.md): Separate events from a single stream into multiple streams using conditional statements, so you can send events to different processors or destinations. - [Sample Processor](https://docs.mezmo.com/telemetry-pipelines/sample-processor.md): Filter incoming events at a configurable 1/N rate to reduce event volume, with conditional rules to always forward matching events. - [Set Timestamp Processor](https://docs.mezmo.com/telemetry-pipelines/set-timestamp-processor.md): Override an event's timestamp with a field and parser of your choice, trying multiple fields and formats until one parses successfully. - [Stringify Processor](https://docs.mezmo.com/telemetry-pipelines/stringify-processor.md): Render an entire event's JSON object into a single text string for downstream steps that require string input, such as the Encrypt processor. - [Throttle Processor](https://docs.mezmo.com/telemetry-pipelines/throttle-processor.md): Apply rate limiting to an event stream to protect downstream destinations, throttling globally or per key field within a configurable time window. - [Trace Sampling Processor](https://docs.mezmo.com/telemetry-pipelines/trace-sampling-processor.md): Sample OpenTelemetry traces at a given rate using the Trace ID, supporting both head-based and conditional tail-based sampling strategies. - [Unroll Processor](https://docs.mezmo.com/telemetry-pipelines/unroll-processor.md): Convert a JSON object array within a field into individual objects, commonly used when a source packages multiple events in a single JSON object. ### Destinations - [Set Up Pipeline Destinations](https://docs.mezmo.com/telemetry-pipelines/set-up-pipeline-destinations.md): Add and connect a destination to your pipeline, and learn how buffering controls when batched events are flushed to the destination. - [Azure Blob Storage](https://docs.mezmo.com/telemetry-pipelines/azure-blob-storage-destination.md): Send Mezmo Pipeline log data to an Azure Blob Storage container with configurable batching, encoding, compression, and prefixes. - [Blackhole](https://docs.mezmo.com/telemetry-pipelines/blackhole-destination.md): A Destination that drops all data sent to it, useful for testing Pipeline data processing in a simulation without billable egress. - [Checkly](https://docs.mezmo.com/telemetry-pipelines/checkly-destination.md): Send Checkly-related spans to Checkly via the OpenTelemetry Destination, using a Route Processor to filter the correct traces. - [AWS CloudWatch Metrics](https://docs.mezmo.com/telemetry-pipelines/cloudwatch-metrics-destination.md): Send Pipeline metrics to AWS CloudWatch for monitoring, with configuration for credentials, compression, namespace, and region. - [AWS CloudWatch Logs](https://docs.mezmo.com/telemetry-pipelines/cloudwatch-logs-destination.md): Send Pipeline logs to AWS CloudWatch for monitoring, with options for credentials, encoding, compression, log group, and stream. - [Datadog Logs](https://docs.mezmo.com/telemetry-pipelines/datadog-logs-destination.md): Send Pipeline log data to Datadog, configuring the API key, compression, and Datadog site region. - [Datadog Metrics](https://docs.mezmo.com/telemetry-pipelines/datadog-metrics-destination.md): Send metrics data to Datadog as Custom Metrics, supported with Datadog Agent, HTTP, and Prometheus Remote Write sources. - [Datadog Traces](https://docs.mezmo.com/telemetry-pipelines/datadog-traces-destination.md): Send Pipeline trace data to Datadog, configuring the API key, compression, and Datadog site region. - [ElasticSearch](https://docs.mezmo.com/telemetry-pipelines/elasticsearch-destination.md): Send indexed log data to an ElasticSearch destination, with options for authentication strategy, compression, endpoints, and indices. - [Google Cloud Storage](https://docs.mezmo.com/telemetry-pipelines/gcp-cloud-storage-destination.md): Send Mezmo Pipeline log data to a Google Cloud Storage bucket with configurable encoding, compression, batching, and credentials. - [Google Cloud Monitoring](https://docs.mezmo.com/telemetry-pipelines/gcp-cloud-monitoring-destination.md): Send metric events to Google Cloud Monitoring, configuring project ID, resource type and labels, and JSON service account credentials. - [Google Cloud Operations](https://docs.mezmo.com/telemetry-pipelines/gcp-cloud-operations-destination.md): Send log events to Google Cloud Operations, configuring log ID, project ID, resource type and labels, and JSON credentials. - [Google Cloud PubSub](https://docs.mezmo.com/telemetry-pipelines/gcp-cloud-pubsub-destination.md): Send events to Google Cloud Pub/Sub, configuring encoding, project ID, topic, and JSON service account credentials. - [Honeycomb Logs](https://docs.mezmo.com/telemetry-pipelines/honeycomb-logs-destination.md): Send log data to a Honeycomb dataset by configuring your Honeycomb API key and target dataset name. - [HTTP Endpoint](https://docs.mezmo.com/telemetry-pipelines/http-destination.md): Send Mezmo Pipeline log data to any HTTP endpoint, with options for encoding, compression, authentication, headers, proxies, and TLS. - [Kafka](https://docs.mezmo.com/telemetry-pipelines/kafka-destination.md): Send Mezmo Pipeline data to Kafka, with options for encoding, compression, TLS, and SASL/SCRAM authentication. - [AWS Kinesis Data Firehose](https://docs.mezmo.com/telemetry-pipelines/kinesis-firehose-destination.md): Publish logs from your Mezmo Pipeline to AWS Kinesis Data Firehose streams using AWS credentials, encoding, and compression settings. - [AWS Kinesis Streams](https://docs.mezmo.com/telemetry-pipelines/kinesis-streams-destination.md): Publish logs from your Mezmo Pipeline to AWS Kinesis Streams using AWS credentials, encoding, compression, and a partition key field. - [Loki](https://docs.mezmo.com/telemetry-pipelines/loki-destination.md): Send logs from your Mezmo Pipeline to any Loki destination, such as Grafana Logs, with configurable endpoint, auth strategy, codec, and labels. - [Mezmo Archive Destination](https://docs.mezmo.com/telemetry-pipelines/mezmo-archive-destination.md): Archive telemetry data to S3 or Azure Cloud Storage in a date-partitioned folder structure so it can later be restored into a Pipeline. - [Mezmo Log Analysis](https://docs.mezmo.com/telemetry-pipelines/mezmo-destination.md): Send Pipeline data to a Mezmo Log Analysis account for search, views, and alerts, with configuration options for ingestion, query, and message fields. - [New Relic](https://docs.mezmo.com/telemetry-pipelines/new-relic-destination.md): Send logs, metrics, and traces to a New Relic instance, configuring the account ID, API endpoint, US or EU region, and license key. - [Notification Channel](https://docs.mezmo.com/telemetry-pipelines/notification-channel-destination.md): Send a Pipeline-triggered notification to Slack, PagerDuty, a Webhook, or Mezmo Log Analysis based on event thresholds over a configurable time window. - [OpenTelemetry Destination](https://docs.mezmo.com/telemetry-pipelines/open-telemetry-destination.md): Open Telemetry Destination configuration - [Prometheus Remote Write](https://docs.mezmo.com/telemetry-pipelines/prometheus-remote-write-destination.md): Send metrics to any destination that accepts the Prometheus Remote Write protocol, such as Grafana, with authentication and endpoint options. - [AWS S3 Storage](https://docs.mezmo.com/telemetry-pipelines/s3-destination.md): Send pipeline data to an AWS S3 bucket for long-term storage, with options for encoding, compression, storage class, and required IAM permissions. - [Splunk HTTP Event Collector](https://docs.mezmo.com/telemetry-pipelines/splunk-hec-logs-destination.md): Send Mezmo Pipeline log data to Splunk via the HTTP Event Collector, configuring endpoint, token, encoding, compression, and indexed fields. - [AWS SQS](https://docs.mezmo.com/telemetry-pipelines/sqs-destination.md): Publish observability events from a pipeline to an Amazon SQS queue, configuring access keys, encoding, region, and queue URL. - [Sumo Logic Logs](https://docs.mezmo.com/telemetry-pipelines/sumo-logic-logs-destination.md): Send logs from a pipeline to your Sumo Logic instance, configuring the collector endpoint, compression, and category. ### Pipeline Management - [Edit or Delete a Pipeline](https://docs.mezmo.com/telemetry-pipelines/edit-a-pipeline.md): Edit Pipeline components and names, compare and roll back revisions, and delete Pipelines through the Mezmo Web App. - [Export and Import a Pipeline Manifest](https://docs.mezmo.com/telemetry-pipelines/export-import-pipeline-manifest.md): Export a SaaS Telemetry Pipeline to a portable YAML or JSON manifest, inspect its required secrets, and import it as a new draft Pipeline through the API. - [Pipeline Event Data Model](https://docs.mezmo.com/telemetry-pipelines/pipeline-event-data-model.md): How events move through a Pipeline via the event envelope, including the message, metadata, and timestamp fields and how to reference them. - [Simulate and Test Pipeline Data Streams](https://docs.mezmo.com/telemetry-pipelines/simulate-pipeline-data-flows.md): Use Simulation mode to test data flow through processors and destinations with sample data, compare input and output with diff view, and add custom samples. - [Set Pipeline Access](https://docs.mezmo.com/telemetry-pipelines/set-pipeline-access.md): Grant organization members access to the pipelines you create by assigning them the Member + Pipeline role. - [The Pipeline Metric Data Model](https://docs.mezmo.com/telemetry-pipelines/metric-data-within-the-pipeline.md): Defines the standard metric data model fields required for processing metrics in a Pipeline, with JSON examples and ways to transform metrics. - [View Pipeline Errors](https://docs.mezmo.com/telemetry-pipelines/view-pipeline-errors.md): Find processing errors in a Pipeline using error indicators, the Error History view, and per-error log lines, plus error retention details. - [Demo Pipeline Overview](https://docs.mezmo.com/telemetry-pipelines/demo-pipeline-guide.md): Walk-through of the auto-created Demo Pipeline showing Route, Filter, and Encrypt Processors handling JSON and financial data. - [Set Threshold Alerts for Pipeline Data Volume](https://docs.mezmo.com/telemetry-pipelines/pipeline-threshold-alerts.md): Create Absolute, Relative, and Absence threshold alerts to be notified when Pipeline ingress or egress volume meets criteria over a time frame. - [Build a Mezmo Telemetry Pipeline with Terraform](https://docs.mezmo.com/telemetry-pipelines/build-pipelines-terraform.md): Use the Mezmo Terraform provider to define, version, and manage your telemetry data Pipelines as infrastructure-as-code. - [Syntax for Editing Pipeline Component Configuration Values](https://docs.mezmo.com/telemetry-pipelines/syntax-for-editing-pipeline-component-configuration-values.md): Learn the syntax for data fields, data references, static values, and metadata when editing source, processor, and destination configuration values. - [Pipeline Example: Kubernetes Telemetry Data Optimization](https://docs.mezmo.com/telemetry-pipelines/pipeline-architecture-for-kubernetes-data-optimizationzlz.md): Walk-through of a Pipeline that transforms Kubernetes telemetry into metrics for observability tools while retaining original data in storage. - [Required Schema for Mezmo Log Analysis Destination](https://docs.mezmo.com/telemetry-pipelines/required-schema-for-mezmo-log-analysis-destination.md): Reference for the message schema, required fields, and display names data must conform to when restoring to the Mezmo Log Analysis destination. - [Azure Event Hub](https://docs.mezmo.com/telemetry-pipelines/kafka-aeh.md): Send Mezmo Pipeline data to Azure Event Hubs through its Kafka endpoint, with broker, topic, TLS, and SASL/SCRAM configuration options. - [How to Create a Shared Source from Scratch](https://docs.mezmo.com/telemetry-pipelines/how-to-create-shared-sources.md): Step-by-step instructions for configuring a new Shared Source, including key management, so it can be reused across multiple pipelines. - [What Are Shared Sources?](https://docs.mezmo.com/telemetry-pipelines/shared-sources-overview.md): Shared Sources are global configurations that transmit the same data across multiple pipelines at once, reducing redundancy and configuration effort. - [Primary Ingestion Pipeline](https://docs.mezmo.com/telemetry-pipelines/the-log-analysis-source-data-pipeline.md): Overview of the optimized log data management Pipeline given to Mezmo Log Analysis customers, including its four processing steps and component configuration. - [How to Convert an Existing Source into a Shared Source](https://docs.mezmo.com/telemetry-pipelines/how-to-convert-existing-source-to-shared.md): Step-by-step instructions for converting an existing pipeline source into a reusable Shared Source without rebuilding it. - [How to Use a Shared Source in a Pipeline](https://docs.mezmo.com/telemetry-pipelines/how-to-use-shared-source-in-pipeline.md): Step-by-step instructions for adding an existing Shared Source to a new pipeline so it inherits all data transmitted through it. - [Sudden Increase in Source Volume](https://docs.mezmo.com/telemetry-pipelines/sudden-increase-in-source-volume.md): Configure an alert that triggers when a source's data volume rises 60% or more compared to a prior tumbling window, including the custom aggregation script. - [OpenTelemetry Collector](https://docs.mezmo.com/telemetry-pipelines/otel-collector.md): Export log, metric, and trace data to Mezmo with the OpenTelemetry Collector, including a quick-start config and Helm chart installation. - [Create Processor Groups](https://docs.mezmo.com/telemetry-pipelines/create-processor-groups.md): Bundle related Processors into a reusable, shareable group to simplify your Pipeline Map and manage their configuration together. - [Percentage Volume Increase](https://docs.mezmo.com/telemetry-pipelines/percentage-volume-increase.md): Example Change Alert configuration that fires when data volume rises by a set percentage compared to the prior tumbling window period. ### Other Topics - [Set Up and Test an HTTP Endpoint Source](https://docs.mezmo.com/telemetry-pipelines/set-up-and-process-http-endpoint-data.md): Walk-through for configuring an HTTP endpoint pipeline source, sending test data with cURL, adding a processor, and routing the data to a destination. - [Grok Pattern Reference](https://docs.mezmo.com/telemetry-pipelines/using-grok-to-parse.md): Learn how to use Grok patterns in Mezmo to extract structured data from unstructured text, including Mezmo-specific patterns, rules, and worked examples. - [Error Code Reference](https://docs.mezmo.com/telemetry-pipelines/error-code-reference.md): Reference of processor, source, and general error codes and their messages for the Mezmo Telemetry Pipeline. - [Archive and Restore Telemetry Data](https://docs.mezmo.com/telemetry-pipelines/archive-restore-data.md): Use the Mezmo Archive Destination and Pipeline Data Restoration Source to store events in S3 or Azure and restore them later. - [In-Stream Alerts](https://docs.mezmo.com/telemetry-pipelines/in-stream-alerts.md): Set threshold, change, and absence alerts on pipeline data to detect and respond to conditions within seconds, before data is indexed or routed. - [Set In-Stream Alerts for Pipeline Nodes](https://docs.mezmo.com/telemetry-pipelines/set-in-stream-alerts.md): Configure threshold, change, or absence alerts on any source or processor node, with evaluation windows and payloads sent to Slack, PagerDuty, or webhooks. - [Example In-Stream Alert Configurations](https://docs.mezmo.com/telemetry-pipelines/example-in-stream-alert-configurations.md): Example configurations for setting up in-stream telemetry data alerts in Mezmo Pipelines. - [Getting Started with the Mezmo Platform](https://docs.mezmo.com/telemetry-pipelines/getting-started-with-the-mezmo-platform.md): Walks you through setting up your organization, building your first telemetry pipeline, creating alerts, and using Mezmo Log Analysis search and visualization. - [API References](https://docs.mezmo.com/telemetry-pipelines/api-references.md): Links to the Mezmo Log Analysis and Telemetry Pipelines API documentation. - [View Event Metrics](https://docs.mezmo.com/telemetry-pipelines/view-event-metrics.md): View historic event volume and trends per app, host, level, and label for a Pipeline over a selected time window. - [Set Surge Detection Alerts](https://docs.mezmo.com/telemetry-pipelines/configure-surge-detection-alerts.md): Configure Surge Detection alerts in the Data Profiler Processor to be notified of significant data volume spikes by app, host, level, or label. - [Tutorial: Create a Basic Data Archiving and Restoration Pipeline](https://docs.mezmo.com/telemetry-pipelines/archive-restore-data-tutorial.md): Step-by-step guide to build archive and restoration Pipelines using an S3 bucket, demo logs, and the Mezmo Log Analysis Destination. - [High Error Rate](https://docs.mezmo.com/telemetry-pipelines/high-error-rate.md): Example threshold alert configuration that triggers when a high number of HTTP 5xx errors per application is detected in metric events. - [Presence of Personally Identifying Information (PII)](https://docs.mezmo.com/telemetry-pipelines/presence-of-personally-identifying-information--pii-.md): Example alert that triggers when the Redact Processor detects PII such as SSNs, email addresses, or custom patterns in telemetry data. - [OpenTelemetry Collector](https://docs.mezmo.com/telemetry-pipelines/otel-collector.md): Export log, metric, and trace data to Mezmo with the OpenTelemetry Collector, including a quick-start config and Helm chart installation. - [AWS CloudWatch Logs](https://docs.mezmo.com/telemetry-pipelines/aws-cloudwatch-logs.md): Use a Lambda function with an HTTP Source to bring AWS CloudWatch logs into your Mezmo Pipeline. - [Checkly](https://docs.mezmo.com/telemetry-pipelines/checkly.md): Ingest Checkly OTLP data into your Pipeline using the OpenTelemetry Traces Source with a URL endpoint and authorization token.