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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - 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Monitor Salesforce logs with Datadog
Mary Jac Heuman, Tom Sobolik · 2021-06-14 · via Datadog | The Monitor blog

Visibility into your Salesforce environment is crucial for keeping your data secure and ensuring a seamless user experience. That’s why we are excited to announce that Datadog can now collect Salesforce event logs via the Event Log File (ELF) API as well as directly from your Real-Time Event Monitoring stream. With more than 50 event types supported via ELF and 14 event types supported via real-time streaming, this integration helps you analyze your logs to get deep insights into the security and operational performance of your Salesforce environment.

Salesforce’s real-time event monitoring records all user actions that occur within your application, and you can supplement this data with requests to the ELF API to access even more event types. Once you’ve connected your Salesforce org to Datadog, Datadog will begin ingesting your Salesforce event logs and automatically parse out key information so you can search, filter, and analyze event attributes. You can specify the events you care about directly in the integration tile to avoid extraneous data. Salesforce data will populate an out-of-the-box dashboard, which you can use to visualize Salesforce activity without any further configuration. You can clone the dashboard to customize and add widgets depending on your needs.

Datadog displays a stream of Salesforce logs and key visualizations in a customizable out-of-the-box dashboard.

In this post, we’ll show how Datadog enables you to monitor, analyze, and alert on key types of Salesforce events, including:

  • user activity, such as user authentication events

  • platform access activity, including API calls and resource creations and deletions

  • security logs that track anomalous activity within your Salesforce application

Monitor Salesforce user activity in real-time

Salesforce events contain detailed information on user actions including logins (LoginEvent), logouts (LogoutEvent), identity verification (IdentityVerificationEvent), and delegated logins by SFDC admins (LoginAsEvent). Datadog’s processing pipeline parses the JSON-formatted logs to extract attributes like the ID of the user, their IP address, and the Salesforce entity that they accessed. Inside the Log Explorer you can query and filter your Salesforce logs using any of these attributes to spot suspicious trends and anomalies. For instance, you could visualize user login events by location to easily see if any are originating from an unexpected location. Or, by visualizing login attempts by user ID, you can easily determine if there are particular users with many failed login attempts.

Visualize user logins by country using the geomap widget and grouping logs by country ISO code.

In addition to monitoring overall trends and anomalous user activity, it’s important to have a granular view of what users are doing within your Salesforce org, like what entities they’re viewing and the types of queries they’re making. Salesforce event logs are identified by a user session key (session_id). With Log Transaction Queries, you can aggregate all logs by one or more shared attributes. In the below example, we’ve aggregated Salesforce logs by session key and counted the unique Event Names. Each grouping represents a user session with a timeline of Salesforce events associated with that session, showing you the complete picture of what actions a user took and exactly what they queried. So, if you find a user gained access to your org after a suspicious number of login attempts, you can pivot to their session to see what actions they took and verify if their activity was legitimate. Using requests to the ELF API, you can access user activity logs on key actions such as searching, running reports, and document and attachment downloads. With records of these actions, you can spot when malicious users were able to access sensitive data.

Use a log transaction query to see what actions a user took during their login session.

Get insight into platform access activity

Along with user activity, it’s important to have visibility into how users are accessing your Salesforce resources. Datadog lets you track and visualize key activity across your Salesforce resources, like which entities users are viewing or querying the most.

You can also monitor and alert on API usage trends to make sure your users don’t run into any issues. For example, creating a forecast monitor on your remaining allowed API calls (salesforce.limits.remaining) ensures you know ahead of time if you are approaching any limits (salesforce.limits.max). Or, you can set an anomaly alert on API operation type over time to alert you to unusual patterns of API activity. Using the dedicated ELF events for REST, SOAP, and Bulk API calls, you can drill down into individual calls to check the credentials of the user who issued them, as well as view their user ID, client IP address, and session key. This way, you can easily identify and track users who are performing suspicious API calls.

Create a forecast monitor to alert you if you’re in danger of approaching API limits.

Detect security threats to your Salesforce org

Salesforce generates events when it detects common security threats and vulnerabilities such as session highjacking and anomalous user activity. In Datadog, you can create Threat Detection Rules to generate a security signal as soon as Datadog receives any of these events.

For instance, Salesforce logs a SessionHighjackingEvent when it detects a possible successful “Man in the Browser” attack, which is when an attacker compromises a user’s browser to obtain their session token and collect sensitive data. Below, we’ve created a rule to trigger when a log containing the evt.name:SessionHijackingEvent attribute appears in Datadog. Since the event log includes the user session ID, you can easily see which session needs to be investigated, and filter for it in the Log Explorer to see which resources were accessed around the time of the attack.

Create a security rule in Datadog to be notified when Salesforce detect a threat to your org.

Datadog also provides out-of-the-box Threat Detection Rules to detect and alert you to other suspicious behavior in your Salesforce org, including:

  • Anomalous number of records deleted

  • Brute-force attack on a user

  • Successful credential stuffing attack after a number of failed user logins

  • Unusually large number of results from a Salesforce query

  • User login from a disabled account

Get started with real-time Salesforce logs today

Salesforce’s ELF API and real-time event monitoring capabilities let you access a broad swath of log reporting data on platform activity across your entire Salesforce environment. With Datadog’s new integration, you can aggregate all of your Salesforce logs to get deep insight into user activity, API usage, and potential threats or vulnerabilities, and correlate that data with telemetry from more than 1,000 other technologies. If you’re already signed up with Datadog, you can connect your Salesforce org today. Or, sign up for your 14-day free trial.