Sep 17, 2018
Reston, VA, USA
Nov 28, 2018   |  By Lawrence Lane
Metricly now supports integration with Consul! Check out our official admin guide. Consul is a service mesh solution that helps with service discovery, configuration, and segmentation functionality.
Nov 27, 2018   |  By Lawrence Lane
Quickly explore your AWS Bill with our new widget! This widget uses the AWS Services Cost report to present cost data on your favorite dashboard. There are three main views for the Cost Explorer Widget: period comparison, service total, and doughnut.
Nov 26, 2018   |  By Lawrence Lane
Metricly now ingests a combination of CloudWatch logs to compute the memory utilization for a given Lambda function, calculated off the max used and billable memory values. Check out the Lambda Sizing Tool Admin Guide for a detailed breakdown of this tool.
Nov 5, 2018   |  By Mike Mackrory
In this article we’ll help you get an understanding of AWS Lambda cost, and how it is calculated. More specifically, we’ll cover the relationships between configuration and cost and help you build strategies to optimize both cost and performance.
Oct 30, 2018   |  By Lawrence Lane
When building a policy that contains multiple metric conditions, users can now use the Match Conditions feature to toggle between validating all of the conditions listed or just any one condition provided. Previously, policies with multiple metric conditions only fired when all listed conditions were met.
Sep 17, 2018   |  By Metricly
Is your performance monitoring using real-time analytics in a way that will produce results or frustration? Real-time analytics can improve the value of performance monitoring by enabling operations teams to pinpoint problems faster and proactively manage applications. If not used correctly or completely, analytics can make or break your monitoring solution.
Sep 17, 2018   |  By Metricly
Get this 12-page essential guide to help you navigate the challenges of cloud monitoring.
Sep 1, 2018   |  By Metricly
When is it appropriate for static thresholds to operate on their own? When should operations teams utilize them as baselines within anomaly detection solutions leveraging machine learning algorithms? Read on to find out.