Elastic Announces Smarter Tail-Based Sampling for APM in Modern Cloud-Native Environments
04 May 2022 - 5:16AM
Business Wire
New Elastic Observability Features Maximize
Visibility While Fine-Tuning the Performance of Data Collection
- Eliminating blind spots by providing fine-grain control over
data collection and storage
- Accelerating troubleshooting for AWS Lambda with the ability to
natively collect serverless traces
- Enhancing visibility across AWS cloud services with new
integrations that speed data ingestion
Elastic (NYSE: ESTC) (“Elastic”), the company behind
Elasticsearch, today announced new features and enhancements across
the Elastic Observability solution to support modern cloud-native
environments, including smarter tail-based sampling for application
performance monitoring (APM) and enhanced visibility across AWS
cloud services.
Eliminating blind spots with Elastic tail-based
sampling
Tail-based sampling can help DevOps and site reliability
engineering (SRE) teams eliminate application performance blind
spots by providing finer-grain control over trace sampling
conditions in high-volume systems with millions of
transactions.
While common head-based sampling that applies a fixed-rate
methodology can be efficient in low-volume application server
environments, tail-based sampling is better suited to more complex,
cloud-native applications. With Elastic tail-based sampling, the
decision to keep or discard a sample is made after a trace has been
completed and observed. As a result, tail-based sampling can help
customers maximize visibility and reduce their data storage costs
by capturing only the most critical transactions.
“As more organizations adopt cloud-native technologies and
microservices-based architectures, application troubleshooting is
becoming increasingly complex,” said Alvaro Lobato, Vice
President, Observability, Elastic. “We built Elastic tail-based
sampling to help customers avoid tradeoffs between full application
visibility and cost. As a result, Elastic Observability provides
maximum visibility while enabling the type of fine-grain control
needed when working in complex, cloud-native environments. ”
In addition, Elastic tail-based sampling enables DevOps and SRE
teams to easily adjust sampling rates to gain greater insight into
application performance by evaluating each trace against a set of
rules or policies and transaction outcomes. The resulting APM
insights can accelerate root-cause analysis for faster time to
resolution.
Enhancing visibility and accelerating troubleshooting across
AWS cloud services
Now generally available, the ability to natively collect
serverless traces from AWS Lambda functions provides customers with
detailed, end-to-end visibility into distributed transactions to
accelerate troubleshooting. Development teams can collect
serverless application traces from Lambda functions written in
Node.js, Python, and Java with a new AWS Lambda APM agent. Elastic
additionally supports native cloud monitoring with the ability to
collect Lambda traces via OpenTelemetry (Java and Python only).
“We're excited to start using Elastic's AWS Lambda APM agent for
our cloud-native applications,” said Jose Navarro, Software
Engineer, Accolade, a healthcare company. “Our team at Accolade
especially likes the fact that it is possible to see whether a
particular invocation of the Lambda function involved a cold start
directly in the trace waterfall chart. The availability of
Lambda-specific metrics, such as cold start rate, at the service
and transaction group levels are also very helpful.”
In addition, customers can now ingest custom logs from Amazon S3
and CloudWatch into Elasticsearch and optionally set up index
templates, ingest pipelines and output specifications. And, with
Elastic 8.2, the Elastic Serverless Forwarder now supports
CloudWatch, Kinesis Data Streams, and direct SQS as additional
input sources for log ingestion. These enhancements give customers
further flexibility by providing ingest options that meet their
existing operating procedures and architectural preferences.
For more information on these and additional feature updates,
read the Elastic blog about what’s new in Elastic Observability
8.2.
About Elastic:
Elastic is a search company built on a free and open heritage.
Anyone can use Elastic products and solutions to get started
quickly and frictionlessly. Elastic offers three solutions for
enterprise search, observability, and security, built on one
technology stack that can be deployed anywhere. From finding
documents to monitoring infrastructure to hunting for threats,
Elastic makes data usable in real time and at scale. Thousands of
organizations worldwide, including Cisco, eBay, Goldman Sachs,
Microsoft, The Mayo Clinic, NASA, The New York Times, Wikipedia,
and Verizon, use Elastic to power mission-critical systems. Founded
in 2012, Elastic is a distributed company with Elasticians around
the globe and is publicly traded on the NYSE under the symbol ESTC.
Learn more at elastic.co.
The release and timing of any features or functionality
described in this document remain at Elastic’s sole discretion. Any
features or functionality not currently available may not be
delivered on time or at all.
Elastic and associated marks are trademarks or registered
trademarks of Elastic N.V. and its subsidiaries. All other company
and product names may be trademarks of their respective owners.
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version on businesswire.com: https://www.businesswire.com/news/home/20220503006258/en/
Chloe Guillemot Elastic Public Relations PR-Team@elastic.co
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