Partners in Instant Observability: Integrations for machine learning, Kubernetes, CI/CD

We recently announced the launch of New Relic Instant Observability (New Relic I/O), an open ecosystem of free, pre-built quickstarts that help engineers start monitoring their stacks in minutes without manual setup. New Relic I/O includes more than 425 quickstarts that bundle necessary building blocks for instrumenting, monitoring, and acting on signals from your telemetry data from the technologies you rely on, such as Kubernetes, CodeStream, and PHP. 

Alongside the quickstarts for popular cloud services, tools, and open standards, leading enterprise software partners also contributed their own integrations and quickstarts to New Relic I/O, making it easy to visualize and monitor all your data in one platform.

New partner quickstarts

The latest cohort of partners contributing to making observability a daily habit for engineers span across CI/CD, Kubernetes testing, and leading machine learning operations (MLOps) platforms. These partners contributed quickstarts in the past month:

• Delphix
• Speedscale
• Amazon SageMaker
• Algorithmia
• Aporia
• Comet
• DAGsHub
• Monalabs
• Superwise
• Truera

Learn more about each of the companies and quickstarts in the next sections.

Instant observability for CI/CD

Delphix is an industry leading data company for DevOps. Their platform provides essential APIs for data provisioning, refresh, rewind, integration, and version control. The Delphix quickstart allows you to get visibility into all your Delphix Virtualization platforms on premises or in the cloud, so that you can rapidly identify and reproduce issues, perform root causes analysis, and dramatically reduce MTTR and downtime.

Instant observability for Kubernetes testing

Speedscale helps Kubernetes engineering teams gain confidence in how new code will perform in real-world scenarios. It provides traffic replay capabilities that help developers discover API issues earlier in their release cycle. Collect and replay API traffic, simulate load or chaos, and measure latency, throughput, saturation, and errors before the code is released. The Speedscale quickstart visualizes traffic replay data into New Relic One dashboards so you can compare this with your telemetry data in New Relic One.

Instant observability for AI/ML model monitoring

New Relic also recently extended our observability experience to provide a new offering for artificial intelligence (AI) and machine learning (ML) teams to break down visibility silos with model performance monitoring. With quickstarts for each of the available MLOps integrations, it’s easy to get complete visibility into ML-powered applications.

Amazon SageMaker enables developers to create, train, and deploy machine-learning (ML) models and to deploy ML models on embedded systems and edge devices. SageMaker supports leading machine learning frameworks, toolkits, and programming languages. With the Amazon SageMaker quickstart you can get a view of the performance metrics, visualize sophisticated ML models, and create a comprehensive monitoring dashboard in New Relic One for your AI/ML applications pipelines.

Algorithmia manages all stages of the production ML lifecycle and accelerates delivery of your ML models into production. It guides a process of continuous optimization across all stages of the ML lifecycle within existing operational processes. With the Algorithmia quickstart, you can instrument, analyze, troubleshoot, and optimize your machine-learning performance across your entire system.

Aporia provides a fast, easy, and secure way for data science teams to monitor their machine learning models in production. Teams can build their own customizable monitors in minutes to receive live alerts for early detection of issues like data drift, unexpected bias, data integrity issues, and performance degradation. With the Aporia quickstart, data scientists and ML engineers receive a combination of cross-platform and integrated smart alerts. These provide a broader picture of the ML infrastructure and an easy, quick way to resolve issues.

Comet is an ML development platform built to meet the intense demands of enterprise teams deploying ML at scale. With Comet’s quickstart, you can manage and optimize your ML models in production from your New Relic One dashboard. Using Comet and New Relic One together, you can accelerate ML development and realize business value faster.

DAGsHub is a platform for data scientists and machine learning engineers to version and sync their data, models, experiments, and code. Your team can easily share, review and reuse your work, providing a GitHub-like experience for machine learning. DagsHub is built on popular open-source tools and formats, making it easy to integrate with the tools you already use like New Relic One. With the DAGsHub quickstart, you can analyze and monitor machine learning training metrics in real-time.

Mona provides complete visibility into your data and models in the real world with the most flexible and scalable AI monitoring platform. Mona’s integration with New Relic One provides next-level monitoring capabilities under a unified production AI environment, from ML models to infrastructure monitoring. With the Mona quickstart, you instantly get alerted on latency issues. It automatically detects anomalies to ensure the best performance within production systems.

Superwise.ai is the company that monitors and ensures the health of AI models in production. The model management platform leverages machine learning at high scale. Their AI assurance solution acts as the one source of truth for all stakeholders. It empowers data science and operational teams with the right insights to scale their use of AI by gaining confidence in their models’ operations and becoming more independent and agile. With the Superwise quickstart, you gain observability and get preconfigured ML monitoring in New Relic One.

TruEra provides best in class AI quality diagnostics and monitoring. With the TruEra quickstart, you go beyond standard accuracy, input and output drift monitoring to identify consequential data drift and other AI quality diagnostics such as fairness, conceptual soundness, and segment behavior. When combined with the comprehensive observability capabilities of New Relic One, MLOps teams can correlate signals throughout the ML lifecycle.

Bring your own ML data into New Relic One

Have another ML stack that you want to integrate with New Relic One? Use the ML Model Monitoring quickstart to bring your own ML model data from any source and integrate ML data with the rest of the application components, including infrastructure.