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Bring your data with you, wherever it lives.

The externaldata operator lets you query data from external storage systems like Azure Blob Storage, AWS S3, or public HTTP endpoints—no imports or pipeline setup required. Whether you’re wrangling lookups from a CSV in cloud storage or tapping into raw JSON logs hosted elsewhere, externaldata lets you treat external files like native Axiom datasets.

This feature is perfect for teams that need fast, one-off access to external reference data or archived logs without moving them into Axiom. Enrich your queries with real-time data joins, lookups, or supplemental context without duplicating storage or breaking flow.

It’s especially handy for:

• Augmenting logs with external user or service metadata
• Merging OpenTelemetry traces with a hosted lookup table
• Running ad hoc analysis on remote JSON, CSV, or TXT files

All it takes is a schema definition and a public URL. Axiom fetches the data and makes it instantly available in your query.

This operator is currently in public preview, and we’re actively working on expanding format support and size limits. Try it out with a simple join or a one-off query to see how much easier data enrichment can be, especially when your data isn’t all in one place.

Check out the externaldata documentation for use cases and examples.

Searching in thousands or even tens of thousands of events at once is no small feat. While a browser’s native search only scans what’s on your screen (due to “virtualization” that prevents performance bottlenecks), Axiom now includes a dedicated search functionality that checks for every result your query returns, even if it’s not yet rendered in the DOM.

Why it matters
Large queries can produce thousands of events, far exceeding what you’d want browsers to render all at once. To keep things running smoothly, applications like Axiom render event rows as needed. However, this makes default browser search fall short, only highlighting the visible rows. We’ve solved that gap by letting you search all query results end-to-end. If your query pulls 10 events, you’ll search across those 10; if it returns 50,000, you’ll search across all 50,000.

Key benefits

• Complete coverage: Spot every instance of the keyword within your query results. No missed matches.
• Effortless navigation: Jump quickly to each match without manual scrolling through massive logs.
• Performance-friendly: Axiom honors any limits you set, so you only search the data you actually need.

How it works
Built into our query results view, the search automatically looks across all returned events. This lets you find hidden insights without switching back and forth or loading more data in your browser tab.

Ready to try it out? Head to our documentation for more details, or jump into the Playground and press Cmd/Ctrl F in the query results view to see how this streamlined search can save you time in debugging and analysis!

Introducing our new lookup operator—the secret sauce to turning your plain logs into rich, insightful data. Gone are the days of tediously piecing together information; now, a simple join brings your data to life. With lookup, you can easily enrich your primary dataset by linking it to a lookup table, giving you the context you need—whether you’re mapping user IDs to profiles or adding extra layers to your security logs. Enjoy a streamlined, intuitive approach to data enrichment that makes your insights not just smarter, but a lot more engaging.

The lookup operator supports both inner and leftouter flavors, offering flexibility to include all records or only matching entries. Its clear syntax and straightforward parameters make it a breeze to integrate into your workflows, ensuring you spend less time on data wrangling and more time on insight-driven actions.

Ready to simplify your data enrichment process? Explore the new lookup operator in our documentation and experience the benefits firsthand.

We’re happy to announce that you can now use the redact APL operator to replace sensitive or unwanted data in string fields with regular expressions.

You can use the redact operator to sanitize log data, obfuscate personal information, or anonymize text for auditing or analysis. The operator allows you to define one or multiple regular expressions to identify and replace matching patterns. You can customize the replacement token, generate hashes of redacted values, or retain structural elements while obfuscating specific segments of data.

The redact operator is useful when you need to ensure data privacy or compliance with regulations such as GDPR or HIPAA. For example, you can redact email addresses, IP addresses, and other personally identifiable information from logs and datasets.

For more information, see redact operator in the documentation.

You can now share Axiom datasets with clients and collaborators.

Dataset sharing allows you to grant query access to your datasets to other Axiom organizations. In addition to directly querying the dataset, the receiving organization can also create other Axiom resources that rely on query access, such as dashboards and monitors.

If you're managing event data for clients, dataset sharing is a great way to empower your client users to self-serve their own insights, while you retain full control over ingest and dataset management.

Dataset sharing is available for all organizations on our Team or Enterprise plans. Check out our documentation to learn how to get started with dataset sharing today.

We’re happy to announce that you can now get an overview of a monitor’s current status, history, and recent viewers.

The monitor status page allows you to:

• View recent activity and history of runs
• View information about monitor configuration
• Check recent viewers of monitor status

For more information, see the documentation on monitor status.

Additionally, Axiom has improved how data is visualized in the Query tab. Previously, it could often be that the summarize statement only returned a table without a chart. You can now use summarize and expect Axiom to better infer the visualization from your query.

We’re happy to announce that you can now resize the span details view. Previously, the size of the span details view was fixed. This meant that for large traces, you could not easily look at the waterfall view of traces and the span details at the same time. You can now resize the view to your needs and easily cross-reference information between the waterfall view and the span details view.

For more information, see the documentation.

We’re excited to announce that we have added seven new IP functions to Axiom Processing Language (APL).

• has_any_ipv4 checks whether a field contains any IPv4 addresses from a specified set of IPv4 addresses.
• has_any_ipv4_prefix checks if an IPv4 address starts with any prefix in a list of specified prefixes.
• has_ipv4 checks if an IPv4 address appears in a specified text.
• has_ipv4_prefix checks if an IPv4 address starts with a specified prefix.
• ipv4_compare compares two IPv4 addresses.
• ipv4_is_in_any_range checks whether an IPv4 address belongs to any range of IPv4 subnets.
• ipv4_is_match checks whether an IPv4 address matches an IPv4 pattern.

We have also added the percentileif aggregation function. It calculates the requested percentiles of a field for the rows where a condition evaluates to true.

For more information, see the documentation.

We’re excited to announce that you can now create continuous flows.

Flows enable you to filter, shape, and route event data to a destination. Previously, you could only create one-time flows, which are one-off operations that process past data for a specific time range and route the output to a destination. You can now create continuous flows, which are continuously running operations that process your incoming data and route the outputs to a destination in real-time.

Axiom Flow is currently in preview. To try it out, sign up for a free preview.

For more information, see the documentation.

We’re happy to announce that you can now set custom comparison time periods for individual dashboard elements.

Previously, each element on a dashboard compared data against the same time period or none. You determined this comparison period at the dashboard level.

You can now set a custom comparison time period for individual dashboard elements that is different from the dashboard’s. For example, the dashboard compares against data from yesterday but individual dashboard elements display data for different comparison periods.

For more information, see the documentation.

We’re excited to announce that you can now set a custom time range for individual dashboard elements.

Previously, each element on a dashboard displayed data for the same time range. You determined this time range at the dashboard level.

You can now set a time range for each element that is different from the dashboard’s time range. For example, the dashboard displays data about the last 30 minutes but individual dashboard elements display data for different time ranges. This can be useful for visualizing the same chart or statistic for different time periods, among others.

For more information, see the documentation.

We’re excited to announce that you can now specify a custom data retention period for each dataset.

The data retention period determines how long Axiom stores your data. By default, the data retention period is defined by your pricing plan and is the same for all datasets. You can now configure custom retention periods for individual datasets that are shorter than your pricing plan’s default retention period. As a result, Axiom automatically trims data after the specified time period instead of the default one defined by your pricing plan. For example, this can be useful if your dataset contains sensitive event data that you don’t want to retain for a long time.

For more information, see the documentation.

We’re happy to announce the introduction of the Query tab.

The Query tab provides you with a unified query builder experience. This change introduces a more logical structure to tabs and implements a clearer separation between the Datasets tab and the Explore tab. Previously, you could run queries in both the Datasets and the Explore tabs. The Query tab now replaces the Explore tab and the query capabilities of the Datasets tab. In this arrangement, the Datasets provides you with information about each field within your datasets, whereas the Query tab allows you to run queries and get deeper insights into your data.

We’re happy to announce the introduction of heatmap dashboard elements.

Heatmaps represent the distribution of numerical data by grouping values into ranges or buckets. Each bucket reflects a frequency count of data points that fall within its range. Instead of showing individual events or measurements, heatmaps give a clear view of the overall distribution patterns. This allows you to identify performance bottlenecks, outliers, or shifts in behavior. For instance, you can use heatmaps to track response times, latency, or error rates.

For more information, see Heatmap dashboard elements in the documentation.

We’re happy to announce that you can now use the _time field with the Vector collector version v0.42.0 or newer.

Before Vector version v0.42.0, the Axiom sink was based on an Elasticsearch endpoint. This constrained Axiom to the Elasticsearch wire semantics. When you sent data to Axiom, you had to specify the timestamp in the @timestamp field.

Starting with Vector version v0.42.0, the Axiom sink uses the native Axiom ingest endpoint. This means that you can specify the timestamp in the _time field as usual.

For more information, see the documentation.

We’re happy to announce that you can now install the Axiom CloudWatch Forwarder with Terraform modules.

The Axiom CloudWatch Forwarder allows you to send logs from Amazon CloudWatch to Axiom. Previously, you could only set it up with AWS CloudFormation stacks. You can now set up the Axiom CloudWatch Forwarder with Terraform modules.

For more information, see the documentation.

We’re excited to announce that you can now add three new elements to your dashboards.

Pie charts can illustrate the distribution of different types of event data. For example, a pie chart can show the breakdown of status codes in HTTP logs.

The note dashboard element adds a textbox to your dashboard that you can customise to your needs. For example, you can provide context in a note about the other dashboard elements.

The monitor list provides a visual overview of several monitors. It offers a quick glance into important developments about the monitors such as their status and history.

For more information, see the documentation on pie charts, notes, and monitor lists.

We’re excited to announce that you can now switch to the event details view by highlighting a specific time range on a chart.

In line charts and heat maps, you can drag the pointer over the chart to highlight a specific time range, and then choose one of the following:

• Zoom enlarges the section of the chart you highlighted. Previously, this was the default behavior.
• You now have the option to click Show events to display events in the selected time range in the event details view.

The time range of your query automatically updates to match what you selected.

We’re happy to announce that you can now easily integrate your Serverless apps with Axiom. Serverless is an open-source web framework for building apps on AWS Lambda. Sending event data from your Serverless apps to Axiom allows you to gain deep insights into your apps’ performance and behavior without complex setup or configuration. Axiom’s pre-built dashboard provides instant insights into your apps’ health and usage patterns.

For more information on setting up the integration, see the documentation.

For more information on the benefits of using the integration, see our blog post.

We’re excited to announce that the audit log is now available on all plans. The audit log allows you to track who did what and when within your Axiom organization. It gives you a complete view of user activity, data access, and changes made to key Axiom resources.

Previously, Axiom manually exported audit data upon request. The audit log is now queryable just like any other dataset. This means that you can build dashboards to track your favorite queries and create monitors to notify you of significant events.

For more information, see the documentation.

We’re excited to announce that Axiom now supports secure, centralized user authentication through the IdP-initiated flow for SAML-based SSO (identity-provider-initiated flow for Security Assertion Markup Language-based single sign-on). Previously, Axiom only supported the service-provider-initiated flow (SP-initiated flow). Axiom now supports both flows.

SAML-based SSO makes it easy to keep access grants up-to-date with support for the industry standard SCIM protocol. This feature is available for Enterprise customers upon request.

We’re happy to announce the introduction of anomaly monitors.

Anomaly monitors allow you to receive an alert when the results of your query deviate from what’s expected. In comparison to threshold monitors, which compare the results of your query against a fixed threshold, anomaly monitors use the recent behavior of the query to determine if the most recent results are anomalous.

For example, suppose you want to monitor response times for a range of API endpoints that you serve. Rather than identifying the correct threshold for each one, you can simply use an anomaly monitor to be alerted whenever there’s a sudden spike in response time. Anomaly monitors allow you to group the results of your query and track expected behavior for each group separately.

For more information, see Anomaly monitors in the documentation.

Creating charts in Axiom has become even easier. We’re excited to announce two improvements to the chart creation process.

Chart creation now includes input validation and in-app education. This assistive feature informs you about the requirements for the type of chart you’re creating, validates your input in real time, and educates you on how to build a query that matches those requirements. Input validation is available for both the visual and the APL query builder.

We have also streamlined the chart creation process to make it more intuitive. Now the first step is to choose the type of chart that you want to create, followed by a chart creation interface tailored to that chart type.

We’re happy to introduce the option to set the default method for null values.

When you run a query with a visualization, you can select how Axiom treats null values in the chart options. For more information, see Configure chart options.

Previously, you had to repeat this procedure for each chart you created. You can now select a default method to deal with null values that Axiom uses in every new chart you create.

For more information, see Profile settings.

We’re excited to announce major improvements to the results table and the event panel.

In the results table, you can switch between raw data and column modes. The raw data mode displays the raw event data and highlights the fields you select. The column mode displays each selected field in a different column and doesn’t show the raw event data. In column mode, you can resize the width of columns by dragging the borders.

In the event panel, you can navigate between events by clicking the Navigate up or Navigate down buttons. You can also change the height of the event panel to fit the viewport height or the height of the results table.

For more information, see the Query results in the documentation.

We’re happy to announce that Axiom complies with the core principles of the Health Insurance Portability and Accountability Act (HIPAA). HIPAA compliance means that Axiom can enter into Business Associate Agreements (BAAs) with healthcare providers, insurers, pharma and health research firms, and service providers who work with protected health information (PHI). Business Associate Agreements (BAAs) are available for Enterprise customers.

We’re thrilled to announce that you can now merge separate visualizations into a single chart. Previously, when you ran a query that produced several visualizations, Axiom displayed the charts separately. This is still the default behavior, but you can now choose to display the separate visualizations in a single chart. This enables you to get a better overview of trends in your data.

For example, the query below displays a different visualization for each percentile specified in the query:

['sample-http-logs']
| summarize percentiles_array(req_duration_ms, 50, 90, 95) by status, bin_auto(_time)

Run in Playground

To merge the separately displayed charts into a single chart, click the View options icon, and then select Merge charts. For more information, see Merge charts.

We’re thrilled to introduce that we’ve added multiple selection to times series charts. Previously, when you held the pointer over rows in the table below a time series chart, the chart displayed the data corresponding to that row. When you moved your pointer away, the chart showed all the data again.

Now you can select the checkboxes on the left of the rows. As a result, the chart only displays the data for the selected rows even if you move your pointer away. This means that your selection sticks until you clear the checkboxes.

Check out the new behavior of the time series charts in the Playground!

Axiom introduces a unified query builder experience in the Explore tab.

• A new toolbar has been added that provides you with all the tools to build your queries.
• The toolbar contains the buttons you could previously find dispersed in different parts of the UI: the time range selector, the button to run your query, and many more.
• Previously, you could only build queries using a visual tool in the Datasets tab or using APL in the Explore tab. Now you can build queries both ways in a single place, the Explore tab. All you need to do is select Builder in the toolbar for a visual query builder experience, and APL to structure queries using Axiom’s piped processing language.

These important updates are part of wider changes that we plan to release soon to improve your query experience.

A year ago, Axiom introduced the search operator to APL to let you explore your data in an unstructured way. While useful, it had limitations in handling complex data types and numbers.

Previously, you could only search for string values. Axiom now significantly expands the search operatorʻs capabilities:

• You can search for numbers. For example, search for a numeric customer ID directly.
• You can search inside complex data types such as maps and arrays.

The has and contains operators power the search operator and also receive these capabilities.

These improvements make it easier to dig deep into your datasets and find the information you need quickly, whether in casual exploration, deep investigation, or advanced monitor and dashboard setups.

Try out the enhanced search capabilities today and experience faster, more comprehensive data exploration. For more details on using the improved search operator, see the documentation.

Axiom users can now use custom webhooks to connect Axiom monitors with their favorite external services.

With the (old) webhook notifier type, it has always been possible to send a POST request to a URL of your choosing whenever a linked monitor triggered. However, the payload of this request had a fixed structure, which required transformation before forwarding to the desired destination.

With custom webhooks, it's now possible to modify the JSON payload, as well as add additional headers for including in the request. Using the Go template syntax, you can conditionally structure the payload depending on the circumstances of the trigger event.

This means that you can easily connect to and authenticate with external services even when they do not have have a dedicated notifier type in Axiom.

For more information, see our documentation.

We’re excited to introduce span links, a powerful feature that allows you to establish relationships between spans, even if they’re part of different traces. Span Links are useful for representing asynchronous operations or batch-processing scenarios where a subsequent operation may start at an unknown time or in a separate trace. By linking spans together, you can preserve the dependencies and connections between these operations.

• Capture asynchronous dependencies: Use span links to associate spans representing asynchronous operations, such as a span triggering a subsequent operation that may start much later or in a different trace altogether.
• Preserve batch-processing relationships: Establish links between spans to capture the relationships in batch-processing scenarios, where operations are processed in bulk and may not have direct connections within the same trace.
• Powerful querying with APL: Leverage the flexibility of Axiom’s Query Language (APL) to find traces with span links. Use the isnotempty(links) condition to quickly identify traces containing linked spans and dive into their details.

Check out the documentation to learn more and get started.

We’re excited to announce the launch of annotations, a new feature that enhances data visualization by allowing you to add contextual markers to charts. With this update, you can now annotate significant events like deployments, server outages, and incidents directly on your charts. This empowers you to easily correlate these events with trends in your data, streamlining the troubleshooting process for issues within your app or system.

Get started by creating annotations through our API and enrich your data analysis experience today. For more information, see Annotate charts.

Axiom introduces match monitors, a new type of monitor that filters for key events and sends them to you.

A monitor is a background task that periodically runs a query that you define and notifies you about the monitor output. Previously, you could only create threshold monitors. Threshold monitors aggregate event data over time, and when the results cross a threshold, Axiom sends you an alert.

Match monitors are a new type of monitor that lets you continuously filter your log data and send you matching events. For example, you set up a match monitor to filter for events where the duration of a request is longer than five seconds or where the level of severity of an error is critical. As a result, Axiom alerts you about every event that matches the filters you set.

For more information, see Monitor data.

We’re excited to introduce the ensure_field() function in APL, a convenient way to ensure the existence of a field and return its value or a typed nil if it doesn't exist. This function simplifies working with fields that may or may not be present in your data, making your queries more robust and reducing the need for complex null checks.

• Field existence check: Checks if the specified field exists in the data and returns its value if it does. If the field doesn't exist, it returns a typed nil based on the provided field type.

• Simplified field access: Access fields without worrying about null values or missing fields. The function handles these cases smoothly, making your queries cleaner and more readable.

• Future-proof queries: Prepare your queries for fields that are expected to exist in the future. For example, you can use ensure_field() to write logic around a field you know will be added soon, ensuring your queries are ready when the field becomes available.

• Migrating schemas: When migrating to a new schema that introduces new fields, ensure_field() can help you write queries that work with both the old and new schemas during the transition period.

Check out the documentation to learn more and get started.

We’re excited to announce the new parse operator in APL, a powerful tool for extracting structured data from string fields. This operator allows you to define parsing patterns using string constants, regular expressions, or a combination of both, and then assign the extracted values to new fields in the result set.

• Data extraction: Extract structured data from unstructured or semi-structured string fields, enabling you to transform raw data into a more usable format.
• Flexibility: Adapt to different data formats and requirements by supporting different parsing modes (simple, relaxed, regex) and providing various options to define parsing patterns.
• Performance: Optimize query performance by extracting only the necessary information from string fields, reducing the amount of data processed and enabling more efficient filtering and aggregation.

Check out the documentation to learn more and get started.

Axiom launches the Axiom Terraform Provider, an Axiom app that lets you provision and manage Axiom resources (datasets, notifiers, monitors, and users) with Terraform. This means that you can programmatically create resources, access existing ones, and perform further infrastructure automation tasks.

Install the Axiom Terraform Provider from the Terraform Registry. To see the provider in action, check out the example.

For a guide that explains how to install the provider and perform some common procedures such as creating new resources and accessing existing ones, see Manage Axiom resources with Terraform. For the full API reference, see the documentation in the Terraform Registry.

Axiom adds support for advanced API tokens.

Advanced API tokens let you perform a wide range of actions in Axiom. When you create an advanced API token, you select which actions you allow the advanced API token to perform. For example, you can create an advanced API token that can only query data from a particular dataset and another that has wider privileges such as creating datasets and changing existing monitors. This lets you assign only those privileges to API tokens that are necessary to perform the actions that you want.

After creating an API token, you cannot change the privileges assigned to that API token.

The API tokens you have previously created continue to function as before. They are now marked as classic tokens and you cannot regenerate them. If your classic API token expires, delete it and create a new one with the same privileges.

For more information, see Tokens.

Axiom adds support for field vacuuming and other improvements.

Field vacuuming wipes all fields and rebuilds the schema on the next event Axiom receives. This can be useful if the number of fields in a dataset exceeds the allowed limits defined by your pricing plan.

To learn more about vacuuming fields, see the documentation.

This release adds the following further improvements:

• Adds the possiblity to set a dashboard as your default starting page in the Axiom app.
• Adds support for searching for datasets in the Datasets, Stream, and Explore tabs.

Breaking changes to Splunk endpoint

This update changes how events received by the Splunk endpoints are stored in Axiom in the following ways:

• Renames the message field to _raw: This adjustment aligns with common data handling practices and improves the intuitiveness of data analysis.

• Includes the fields object in requests: Requests to the Splunk endpoint include the fields object to provide more comprehensive data capture.

Action required

If you use saved queries, dashboards or monitors for datasets associated with a Splunk endpoint, make the following changes on March 11th, 2024:

• Rename the message field to _raw in the affected queries.
• Ensure new fields do not collide with existing aliases or virtual fields.

We are excited to announce the union operator in APL, a powerful operator designed to enhance the merging of event data from multiple sources into a single dataset.

• Enhanced data combination: Easily merge rows from different datasets, creating a unified view of your event data.

• Simplified querying: Make your data querying easier by combining related or complementary datasets with a single operation.

• Improved data management: Handle complex datasets more effectively, allowing for more comprehensive data insights.

Check out the guide to learn more and get started.

Axiom lets you set up a notifier with Microsoft Teams and adds other improvements to notifiers.

The new notifier lets you integrate your monitors with Microsoft Teams. When a monitor triggers, you now have the option to send a notification to your organization’s Microsoft Teams instance.

This release adds the following further improvements to notifiers:

• Adds a Test button to the right of each notifier in the list of notifiers. Clicking this button triggers the notifier for a single test run. Use this feature to ensure a notifier works as intended.
• Adds the possibility to manage notifiers from the list of monitors. Previously, if you started creating a monitor but realised you hadn't created the notifier, you had to leave the monitor creation process. After this update, you can create notifiers without leaving this page.

To explore the new notifier features, go to your Axiom account.

Axiom adds a span duration histogram and other improvements to tracing.

The span duration histogram gives you a quick overview about the duration of individual spans within a trace. This histogram appears to the right of the waterfall view of traces. The span duration histogram can be useful in the following cases, among others:

• You look at a trace or an individual span and you only know its duration. There is no obvious error. You want to know if you are looking at something normal in terms of duration, or an outlier. The histogram helps you determine if you are looking at an outlier and might drill down further.
• You've found an outlier. You want to investigate and look at other outliers. The histogram shows you what the baseline is and what is not normal in terms of duration. You want to filter for the outliers and see what they have in common.

This release further improves tracing in the following ways:

• Adds support for deep linking to individual span inside a trace.
• Adds support for expanding multiple span events.
• Adds support to export traces in Axiom and Jaeger format.
• Improves the design of the trace waterfall view. With tighter data density, you can scan more spans efficiently.
• Improves the background contrast on span hover and click for readability.
• Changes search across spans so that it is now case insensitive.
• Fixes an issue where missing spans were duplicated if they had multiple children.
• Fixes an issue where child spans were displayed larger than their parent span due to rounding.

In addition, this release fixes an issue where the Grafana data source plugin couldn't query data from Axiom.

To explore the new tracing features such as the span duration histogram, go to the Axiom Playground and click a trace in the list.

Axiom lets you determine geo information like country, latitude, and longitude from an IP address.

If your event data contains a field with an IP address, you can now augment the event with geographical information with the geo_info_from_ip_address function in the Axiom Processing Language (APL). This function extracts geographical, geolocation, and network information. It supports both IPv4 and IPv6 addresses.

For more information, see the documentation on geo_info_from_ip_address.

This release adds a sidebar to the Datasets and Explore tabs where you can select the fields you want to display in the results table. Previously, you could only see the raw data in the results table. This prevented you from focusing exactly on the fields you were interested in. The new sidebar enables you to customize the results table and to see exactly the fields that are important to you.

The fields sidebar shows the number of distinct values in each field. This can help you determine the most suitable aggregation method in your analysis.

Explore the fields sidebar in the Axiom Playground

We've introduced an Event Timeline to Axiom, providing a bird’s eye view of your query results that helps identify spikes, dips, and trends. With one click, you can enable a visual representation of the number of events across a time window.

• Swift insights and event identification: Get an immediate understanding of event distribution over time and easily pinpoint specific events, patterns, or anomalies with the clear visual representation.

• Time range customization: Focus on what’s important by adjusting the time range of your query directly from the histogram.

Simply select your dataset, run a query, enable the Event Timeline, and refine your time range as needed.

Check out the documentation to learn more.

We are excited to announce the latest updates to Axiom’s user interface, making it more user-friendly and accessible than ever before. With a consistent design across the platform, this release focuses on enhancing visual clarity and improving user experience. Here’s what’s new:

• Compact UI: We've refined the interface for a cleaner look and enhanced data density, meaning you can see more on your screen without sacrificing readability.

• Improved contrast: Upgraded theming tokens for better visibility in light and dark modes.

We are excited to introduce field value auto-completion in APL queries, enhancing your query writing experience by providing suggested field values as you type. This feature is designed to boost productivity and reduce errors while writing and managing queries.

An example using the where operator and string operator is included in the image above. As you type your query, the possible values for the method field appear automatically, allowing you to select the correct value quickly.

Our goal is to help you explore data faster, and this is one enhancement that should help with that.

We’re excited to announce the new search operator in APL, a special operator that enhances data search capabilities by performing full-text scans over specified datasets. Instead of limiting you to particular fields or conditions, this feature allows for a broad search across multiple fields.

• Versatility: Search for a specific text or term across various fields within a dataset, without the need to specify each field.

• Efficiency: Save time by quickly locating the data you need.

Check out the documentation to learn more and get started.

We’re excited to announce the enhanced next-axiom library, updated and optimized for Next.js 13. Here are the updated features:

• Integrated AxiomWebVitals for performance metrics.
• Enhanced logging for client/server components and route handlers.
• Comprehensive upgrade guide for transitioning from Next.js 12.

Check out the documentation to learn more and get started.

Axiom Processing Language (APL) is a robust and powerful query language that facilitates the extraction of in-depth insights from your vast pools of data. Be it logs, events, analytics, or other forms of machine data, APL empowers you with the adaptability to filter, transform, and meaningfully summarize your information.

We are continuously enhancing APL by introducing novel functions to optimize your data querying process.

• format_url(): Improves string formatting into valid URLs.
• pair(): Returns a key-value pair separated by specified delimiter.
• parse_pair(): Returns a key-value pair separated by Seperator in Pair. If absent, returns Pair with an empty key.
• array_select_dict(): Selects a dictionary from an array of dictionaries.
• coalesce(): Returns first non-null or non-empty expression from a list evaluation.
• sample operator: Selects random rows for exploration

Check out the APL documentation to learn more.

We’re excited to announce the latest addition to Axiom Dashboards: Table charts functionality, specifically designed to enhance data analysis. Table charts are powerful, enabling you to visualize, analyze, and present complex data with ease. Table charts support common data types, including numerical, textual, and categorical, making it a versatile tool for any analytics workflow.

The current implementation allows you to work with generic data to get valuable insights. This is just the beginning! We have more enhancements in the pipeline arriving soon.

We appreciate your continued feedback on this update within our Discord Community.

AWS PrivateLink allows you to access Axiom securely over the AWS network directly from your VPC without needing an internet gateway or NAT device, simplifying your network setup. Enterprise customers can also opt-into connecting two VPCs within the same region or across different regions, providing a secure and private connection for communication using VPC peering.

For more information about connecting to Axiom over AWS PrivateLink on Enterprise, or if you require support for VPC peering, please contact our sales team.

Kickstart your Axiom journey with our Getting Started walkthrough that guides you step-by-step through the initial setup and onboarding process.

You'll discover how to get up to speed faster and maximize Axiom’s powerful features, like streaming, exploring, and monitoring your data, ensuring a quicker and more seamless experience.

Get started with the onboarding process.

We receive thoughtful product improvement suggestions from our community on Discord all the time. One popular request has been to add dark mode.

We’re delighted to tell you it’s now landed!

You’ll find the option under the top-right menu. It can follow the system theme or force light or dark mode.

Join the Discord and help shape the future of Axiom.

We recently analyzed comments from new users and existing customers about our product documentation. We carefully considered the feedback, then used it to improve navigation in our help system.

These changes have just landed! This is a significant improvement to our document navigation making it even easier for you to find the information you need.

It’s not the end of the road though, we have more work to do, which will land shortly. We welcome your ongoing thoughts on this update in our Discord Community.

Axiom’s new chart variant area enables you to identify log patterns and generate advanced visualizations from your logs using stacked charts. With stacked charts, you can discover trends and compare query patterns from your log data visualization in relative time.

Stacked charts are stacked on top of each other, and by using stacked charts, you can now aggregate your query accurately.

Check out the documentation to learn more.

The Secure Syslog integration now supports web and application logging from cloud application platforms like Render. The Syslog endpoint allows users to send and visualize event logs from static sites, web service, and application workers in just a few clicks.

With this Syslog and Render integration you can:

1. Monitor your static sites
2. Collect and track all available performance logs in your web service
3. Filter errors and sort your logs using Axiom Processing language

Learn more about how to use Secure Syslog on Render.

Axiom Processing Language (APL) is a query language that is perfect for getting deeper insights from your data. Whether you’re working with logs, events, analytics, or other machine data, APL provides the flexibility to filter, transform, and summarize effectively.

We keep making APL better by introducing new functions to improve your data query experience.

Statistical Functions

• make_list()

• make_list_if()

• make_set()

• make_set_if()

Check out the documentation to learn more.

To make APL Queries easier to work with we now support Query Options like strict types to silently enable type hinting for compatible data types behind the scenes.

For example, in normal operation, a field containing a mix of floats and integers can be worked with as if they are all numbers. However, there are times where you want to disable all such conversions, and then strict types query option lets you do this.

Learn more about APL Set Statement

ℹ️ The latest release of axiom-js adds support for the winston logging library:

• Connect one of the best logging libraries for node to Axiom
• Use structured logging to take advantage of Axiom’s advanced querying

Get started here

Collect, transform, and route all your logs, metrics, and traces from Vector and set up Axiom as a sync for your observability data.

With the Vector integration, you can:

• Send data to Axiom from any source
• Ingest and analyze large volumes of data
• Build share queries, build dashboards, setup alerting, and much more

Get started

💡: You can export your middleware, edge, or api Vercel functions withAxiom() to:

• Access logging from the request object
• Capture request properties such as query params etc
• Inspect failed executions with all the details you need

⚡️ Vercel Edge Function support is now live!

All integration users automatically see Edge Function request data from today 📈

For the best experience, upgrade your next-axiom to >= v0.12.1 and use the per-request logging functions:

Get Started

next-axiom now supports @nextjs middleware!

You can now fully:

• Observe all middleware calls
• Measure performance, errors, cache usage
• Log errors & warnings with full structured logging

Get started here

A few weeks ago, we launched our Vercel integration and joined the Vercel marketplace. Axiom provides you with Persistent logging and performance metrics for your Vercel applications and Next.js projects. The Axiom integration enables you to monitor the health and performance of your Vercel deployments by ingesting all your request, function, and web vitals data.

You can use Axiom’s pre-built dashboard for an overview across all your Vercel logs and vitals, drill down to specific projects and deployments, and get insight on how functions are performing with a single click.

You can get and perform other functionalities on your Vercel Applications like:

• Request, function, & static logs
• Function performance + insights
• Custom queries, notifications & alerts
• Unsampled Web Vitals

Install Axiom on your Vercel applications to monitor the health and performance of your deployments

You can now set up and configure a lambda function to run queries using an Application Load Balancer on AWS. Running queries on AWS Lambda can result in lower costs and better performance.

Setting up and Configuring Lambda Queries only applies to Axiom Self-Host installs

Learn more about configuring lambda queries

We worked on and deployed a new topk implementation with a scaling factor. With this implementation, you can get the precise estimates when you want to know the top 5 or top 10 (where ‘5’ and ’10’ are ‘k’ in the topk) values for a field in a dataset.

The topK aggregation takes two arguments:

1. The field to aggregate
2. How many results to return (top 5, or top 10, or top 20, etc)

Learn more about this aggregation here

We enabled and deployed one-click login on CLI. With this, you can log in to your Axiom deployments and account resources directly on your terminal using the Axiom CLI.

Read the documentation on enabling One-Click Login

We deployed the latest version of our REST API docs here. All the endpoints live under the url https://app.axiom.co/api and follow the REST architectural style.

Currently, we documented the endpoints for:

• Datasets
• Querying
• Orgs
• User

Explore the REST API Documentation here

With the new icons on timestamp and virtual fields you can now view the timestamp icon on _time on your field list drop-down on Axiom Data Explorer.

With the latest UI Changes, you can now upload gzipped files using the .gz filename convention.

Click the upload button and drag or drop the file in the box in the Dataset UI

Topk Explore

Using the topk explore button, you can get queries of your specific visualisation directly on Data Explorer.

We added the Cancel button on Analytics and Data Explorer for you to cancel queries and update your changes.

You can now view and copy your organization ID on your Settings page on your Axiom Account. Your Organization ID is under your organization name. Your Ogranization ID must be provided in case a Personal token is used for Axiom CLI and the Client Libraries. It’s not needed when using an API Token.

Your organization’s Avatar is better using the initials of your org.

Get Notified before deleting Token

With the new changes, you will can get the specific detials of your API and Personal Token before delting them on the dashboard.

The Axiom Processing Language (APL) is a query language that is perfect for getting deeper insights from your data.

We keep making APL better by introducing new functions for your data.

• array_concat()
• array_iff()
• array_index_of()
• array_length()
• array_reverse()
• array_rotate_left()
• array_rotate_right()
• array_slice()
• array_split()
• array_sum()

IP Functions

• ipv4_is_in_range()
• ipv4_is_private()
• ipv4_netmask_suffix()

Hash Functions

• hash_md5()
• hash_sha256()
• hash_sha1()

Get notification on query time range before the earliest event or after the latest event

In your Dataset dashboard, you can now see a notification if your query time range begins after the dataset received its last event.

• And a notification if your query time range ends before the dataset received its first event

Our Vercel integration is live but still in beta. using this integration you can analyze, stream, and run queries from your Vercel applications and resources directly on Axiom.

Get in touch with the team to try it out

APL datetime fields are now fully supported

Datetime fields are fully supported on APL, literals of type datetime have the syntax datetime (value), where a number of formats are supported for value.

Read more here

APL: improved support for null types

We have improved support for null types, the scalar function isnull can be used to determine if a scalar value is the null value. The corresponding function isnotnull can be used to determine if a scalar value isn't the null value.

Read more about this feature here

Axiom Data Explorer provides a full auto-completion environment for getting deeper insights from your data. Whether logs, events, analytics, or similar, APL provides the flexibility to filter, manipulate, and summarize your data exactly the way you need it.

The newly published tutorial includes lots of helpful links and guide on how you can discover valuable insights, explore, store, run super-fast queries and monitor high volumes of fresh and historical structured data using Axiom Data Explorer.

Learn about enabling comprehensive monitoring using Axiom Data Explorer

Dashboards are now accessible on Axiom Play. It is a read only dashboard experience that provides you with query information across multiple datasets which are visualized in one place.

Explore this feature