nMachine is an end-to-end platform-building solution. Create ultra-bespoke tooling that streamlines engineering processes, and replaces expensive tools.
Get StartedCasual to Hardcore Pages
Build your teams the consolidated operations platforms they need to ship better software faster.
Operation Logic
Build your teams the consolidated operations platforms they need to ship better software faster.
Become a Design Partner
Build your teams the consolidated operations platforms they need to ship better software faster.
Dedicated features for the end-to-end process - from collecting data, to logic-writing, to page-building.
Observability, Logs, Errors
Engineering Intelligence
Cost Intelligence
Self-Service & Cataloging
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Populate your always-in-sync data lake with telemetry from OpenTelemetry, resources from Kubernetes, GitHub, Jira, Helm, AWS, and GCP, and spend data via the new FOCUS protocol. Customize your schema, create relationships within and across different types of data.
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Use the logic editor to query and perform general calculations on your Engineering Data Lake data. Use your results to create standards, goals, and alerts. Organize your custom logic into a familiar paradigm of instance and collection methods, e.g repo.unclosed_tickets().
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Create different types of UIs for different types of roles and levels of abstraction. Invoke your reusable logic to move fast. Use barebones widgets for greater control, or prebuilt templates for common use cases. Build whatever makes sense for your teams and workflows.
Compute the insights and promote the standards that matter across your Engineering Data
Lake, however advanced.
Query Resources, Metrics, Logs, Traces, and Spend.
Write Instance and Collection methods to extract insights from your Engineering Data Lake.
Create Mixed Timeseries Signals from your Queries.
Model your timeseries into a type-agnostic format that supports a large family of built-in statistical operations.
Create Goals by invoking your Timeseries Signals.
Use your signals to create goals, deadlines, and requirements against your data. Goals can be specific to resources or global.
Set Standards by invoking your Timeseries Signals.
Use your signals to create health checks, standards, and alerts against your data.
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Build tooling around your people and processes, not the other way around.
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Synchronize Attention & Effort
Help different kinds of engineers and leaders see a consolidate picture of the problems they are solving and goals they are pursuing.
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Drive Change, Showcase Progress
Mix in standards & goals, general application Bring in your key metrics, as well as the standards defined for your team, and create a shared a view of progress and accountability for everyone.
Create Specialized Pages for Specialists
Give engineers the traditional observability, error tracking, logging, cost analysis, and APM they are used to accessing across different tools.
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Relate Otherwise Disconnected Signals
Bring together data typically owned by different teams into one place. Make it easier to delegate action in when dealing with inherently cross-functional matters.
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Create Generalist Pages
Mix in standards & goals, general application performance, basic cost, and quick resource links. Build pages closely tailored to particular roles, or general pages for the whole team.
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Create a single predictable experience. Defrag your tooling stack. Get
operational faster.
Create gorgeous pages with rich widgets and layouts in minutes.
Mix whatever data makes sense.
Blank canvases to build whatever helps your teams solve their problems.
Custom Detail & Collection pages for any resource in your Engineering Data Lake.
Rich forms with input widgets to call your tasks, giving users self-service access.
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Connect to everything needed to paint a complete data picture of your app during and
after development.
Sync your Compute Engine Instances, Cloud Functions, GKE Clusters, SQL Databases, Cloud Builds, Artifact Registries, and more to come.
Import data that paints the picture of your source code and engineering. Sync your Repos, Commits, Pull Requests, Tags, and People.
Import your billing data in FOCUS format from GCP, AWS, and more to come.
Sync the major resource types from any cluster, including Deployments, Pods, HTTP Routes, Ingresses, and more.
Ingest Metrics, Logs, and Traces from OpenTelemetry collector on any cloud or On Prem. Use our Helm Charts to deploy collectors in your Kubernetes or point your existing ones to your nMachine.
Import data that paints an accurate picture of your engineering movement: Sprints, Tickets, and Epics. Combine with GitHub and Helm for an even richer picture.
Get the most accurate picture of your release practices possible by connecting to Helm and importing revisions data.
Connect to your Terraform Cloud account and create new instances or environments of your application directly from inside your nMachine.
Sync your EC2 Instances, Lambda Functions EKS Clusters, SQL Databases, S3 Buckets, and more to come.
Platform created for the people
Your Engineering Data Lake is yours to customize and build reusable logic on top of.
Platform created for the people
Your Engineering Data Lake is yours to customize and build reusable logic on top of.
OpenTelemetry Metrics, Logs, and Traces
OpenTelemetry data is stored in a PromQL/SQL-queryable Clickhouse database. Create custom labels, as well as label mappings to resources in your Engineering Data Lake. Create instance and collection mathods from resources to telemetry data, making it easy to get compute telemetry insights at the resource level.
FOCUS Billing Data
Your cloud provider's billing data data is imported and stored using the new FOCUS standard for cloud billing data. Map billing data to resource kinds, create instance methods to easily get resource-level insights. Take advantage of resource associations to get a view of indirect costs, per-person costs, and other otherwise hard to compute insights.
️Resources from Kubernetes, Jira, GitHub, and more
Clusters, Repos, Builds, Sprints, and many more resources are represented as records in a database. You can modify its schema in seconds, create custom resources, add triggers and custom population logic. Once your data is modeled correctly, you can create instance and collection methods on resources, such as queries and other calculations.
Resources from Kubernetes, Jira, GitHub, and more
Clusters, Repos, Builds, Sprints, and many more resources are represented as records in a database. You can modify its schema in seconds, create custom resources, add triggers and custom population logic. Once your data is modeled correctly, you can create instance and collection methods on resources, such as queries and other calculations.
OpenTelemetry Metrics, Logs, and Traces
OpenTelemetry data is stored in a PromQL/SQL-queryable Clickhouse database. Create custom labels, as well as label mappings to resources in your Engineering Data Lake. Create instance and collection mathods from resources to telemetry data, making it easy to get compute telemetry insights at the resource level.
FOCUS Billing Data
Your cloud provider's billing data data is imported and stored using the new FOCUS standard for cloud billing data. Map billing data to resource kinds, create instance methods to easily get resource-level insights. Take advantage of resource associations to get a view of indirect costs, per-person costs, and other otherwise hard to compute insights.
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