{"id":2792,"date":"2026-05-13T09:16:37","date_gmt":"2026-05-13T13:16:37","guid":{"rendered":"https:\/\/shirishranjit.com\/blog1\/?page_id=2792"},"modified":"2026-05-13T09:16:40","modified_gmt":"2026-05-13T13:16:40","slug":"aapache-devlake-pia-synopsis-security-data-flows-and-risks","status":"publish","type":"page","link":"https:\/\/shirishranjit.com\/blog1\/architect-principles\/aapache-devlake-pia-synopsis-security-data-flows-and-risks","title":{"rendered":"aApache DevLake \u2013 PIA Synopsis (Security, Data Flows, and Risks)"},"content":{"rendered":"\n<h1 class=\"wp-block-heading\"><br \/><\/h1>\n\n\n\n<style>\n        :root {\n        --accent: #464feb;\n        --timeline-ln: linear-gradient(to bottom, transparent 0%, #b0beff 15%, #b0beff 85%, transparent 100%);\n        --timeline-border: #ffffff;\n        --bg-card: #f5f7fa;\n        --bg-hover: #ebefff;\n        --text-title: #424242;\n        --text-accent: var(--accent);\n        --text-sub: #424242;\n        --radius: 12px;\n        --border: #e0e0e0;\n        --shadow: 0 2px 10px rgba(0, 0, 0, 0.06);\n        --hover-shadow: 0 4px 14px rgba(39, 16, 16, 0.1);\n        --font: \"Segoe Sans\", \"Segoe UI\", \"Segoe UI Web (West European)\", -apple-system, \"system-ui\", Roboto, \"Helvetica Neue\", sans-serif;\n        --overflow-wrap: break-word;\n    }\n\n    @media (prefers-color-scheme: dark) {\n        :root {\n            --accent: #7385ff;\n            --timeline-ln: linear-gradient(to bottom, transparent 0%, transparent 3%, #6264a7 30%, #6264a7 50%, transparent 97%, transparent 100%);\n            --timeline-border: #424242;\n            --bg-card: #1a1a1a;\n            --bg-hover: #2a2a2a;\n            --text-title: #ffffff;\n            --text-sub: #ffffff;\n            --shadow: 0 2px 10px rgba(0, 0, 0, 0.3);\n            --hover-shadow: 0 4px 14px rgba(0, 0, 0, 0.5);\n            --border: #3d3d3d;\n        }\n    }\n\n    @media (prefers-contrast: more),\n    (forced-colors: active) {\n        :root {\n            --accent: ActiveText;\n            --timeline-ln: ActiveText;\n            --timeline-border: Canvas;\n            --bg-card: Canvas;\n            --bg-hover: Canvas;\n            --text-title: CanvasText;\n            --text-sub: CanvasText;\n            --shadow: 0 2px 10px Canvas;\n            --hover-shadow: 0 4px 14px Canvas;\n            --border: ButtonBorder;\n        }\n    }\n\n    .insights-container {\n        display: grid;\n        grid-template-columns: repeat(2,minmax(240px,1fr));\n        padding: 0px 16px 0px 16px;\n        gap: 16px;\n        margin: 0 0;\n        font-family: var(--font);\n    }\n\n    .insight-card:last-child:nth-child(odd){\n        grid-column: 1 \/ -1;\n    }\n\n    .insight-card {\n        background-color: var(--bg-card);\n        border-radius: var(--radius);\n        border: 1px solid var(--border);\n        box-shadow: var(--shadow);\n        min-width: 220px;\n        padding: 16px 20px 16px 20px;\n    }\n\n    .insight-card:hover {\n        background-color: var(--bg-hover);\n    }\n\n    .insight-card h4 {\n        margin: 0px 0px 8px 0px;\n        font-size: 1.1rem;\n        color: var(--text-accent);\n        font-weight: 600;\n        display: flex;\n        align-items: center;\n        gap: 8px;\n    }\n\n    .insight-card .icon {\n        display: inline-flex;\n        align-items: center;\n        justify-content: center;\n        width: 20px;\n        height: 20px;\n        font-size: 1.1rem;\n        color: var(--text-accent);\n    }\n\n    .insight-card p {\n        font-size: 0.92rem;\n        color: var(--text-sub);\n        line-height: 1.5;\n        margin: 0px;\n        overflow-wrap: var(--overflow-wrap);\n    }\n\n    .insight-card p b, .insight-card p strong {\n        font-weight: 600;\n    }\n\n    .metrics-container {\n        display:grid;\n        grid-template-columns:repeat(2,minmax(210px,1fr));\n        font-family: var(--font);\n        padding: 0px 16px 0px 16px;\n        gap: 16px;\n    }\n\n    .metric-card:last-child:nth-child(odd){\n        grid-column:1 \/ -1; 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The core service has no built-in user management, so <strong>never expose it publicly<\/strong>. Use Grafana\u2019s authentication and DevLake\u2019s Config UI (with basic auth) over internal network only, aligning with SOC 2 access control practices.<\/p>\n  <\/div>\n  <div class=\"insight-card\">\n    <h4>Protect Credentials &#038; Data Flows<\/h4>\n    <p>DevLake connects to Jenkins, Jira, SonarQube, Bitbucket via API tokens. These <strong>credentials are stored encrypted<\/strong> in DevLake\u2019s database (protected by an <code>ENCRYPTION_SECRET<\/code>). Mitigate risk by using least-privilege tokens, securing the encryption key, and monitoring data flows to prevent unauthorized access or data leaks.<\/p>\n  <\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Overview of Apache DevLake and Data Flows<\/h2>\n\n\n\n<p>Apache DevLake&nbsp;is an open-source platform that&nbsp;ingests and analyzes data from DevOps tools&nbsp;(source control, CI\/CD, issue trackers, code quality platforms) to produce engineering productivity metrics. It functions as a data lake for development pipelines: DevLake&nbsp;collects data via plugins&nbsp;from tools like&nbsp;Jenkins, Jira, Bitbucket, and SonarQube, then stores and transforms this data in an internal database for analysis. The&nbsp;data flow&nbsp;is as follows:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>DevLake pulls data from each integrated tool\u2019s API (e.g. build results from Jenkins, tickets from Jira).<\/li>\n\n\n\n<li>Raw API responses are stored (JSON) in a\u00a0\u201cRaw\u201d layer.<\/li>\n\n\n\n<li>Data is then parsed into tool-specific tables (the\u00a0\u201cTool\u201d layer) and finally unified into a common\u00a0\u201cDomain\u201d layerschema for cross-tool metrics.<\/li>\n\n\n\n<li>A\u00a0MySQL\/PostgreSQL database\u00a0holds all processed data (both DevLake metadata and the imported DevOps records).<\/li>\n\n\n\n<li>Grafana dashboards\u00a0(or other BI tools) query the DevLake database\u2019s domain layer to visualize KPIs like deployment frequency, lead time, issue backlog, bug rates, etc..<\/li>\n<\/ul>\n\n\n\n<p>Importantly,&nbsp;DevLake does not collect business transaction data or customer personal data&nbsp;\u2013 it deals with engineering data such as code repository activity, CI pipeline logs, ticket statuses, and code quality findings. This significantly limits privacy impact. However, note that some&nbsp;personal data about developers&nbsp;(e.g. commit author names, ticket assignees) may appear in the collected data. These are internal to your organization and should be handled under normal employee data privacy policies.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Security Considerations (SOC 2 Alignment)<\/h2>\n\n\n\n<p>Deploying DevLake internally can be configured to align with&nbsp;SOC 2&nbsp;security principles by implementing strong access controls, encryption, and monitoring:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Access Control &amp; Authentication:\u00a0DevLake\u2019s core API service has\u00a0no built-in user accounts or role-based access, so access must be controlled externally:\n<ul class=\"wp-block-list\">\n<li>The recommended approach is to\u00a0run DevLake in a trusted internal network\u00a0(e.g. within an Azure VNet or private subnet) and\u00a0do not expose DevLake\u2019s API port\u00a0publicly. Only the Grafana UI (for dashboards) should be accessible to end users, and even that access can be restricted to a VPN or corporate network segment.<\/li>\n\n\n\n<li>Grafana\u00a0(the primary dashboard interface) supports user authentication and role-based access control. Configure Grafana with your enterprise SSO or user directory so that only authorized team members can view DevLake dashboards.<\/li>\n\n\n\n<li>The DevLake\u00a0Config UI\u00a0(used for setting up data connections and pipelines) should be protected via its built-in HTTP Basic Auth (using\u00a0<code>ADMIN_USER<\/code>\/<code>ADMIN_PASS<\/code>). Set strong credentials and limit access to this configuration interface to administrators. (The Config UI is not designed for broad use.)<\/li>\n\n\n\n<li>Enforce the principle of\u00a0least privilege: only grant DevLake (and by extension, Grafana) access to users who need to view these engineering metrics. This aligns with SOC 2 requirements to restrict system access to authorized individuals.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Network Security:\u00a0Since DevLake will run on\u00a0Azure infrastructure, leverage Azure\u2019s controls to isolate and protect it:\n<ul class=\"wp-block-list\">\n<li>Deploy DevLake components (the API server, database, Grafana) in a secure environment (e.g. an Azure Kubernetes Service cluster or VM network) and use Network Security Groups or firewall rules to allow traffic only from necessary sources (e.g. Grafana connecting to the database, admins connecting to the Config UI).<\/li>\n\n\n\n<li>Use\u00a0TLS\/HTTPS\u00a0for any web interfaces (Grafana, Config UI), especially if there\u2019s any access outside a fully private network. Also ensure DevLake\u2019s connections to data sources (Jira, Jenkins, etc.) use HTTPS endpoints to encrypt data in transit.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Encryption:\u00a0DevLake\u2019s database contains all the collected DevOps data and also sensitive connection info (like API tokens for Jira, Jenkins, etc.). Ensure\u00a0encryption at rest\u00a0for this database. (If using Azure\u2019s managed MySQL\/Postgres, enable storage encryption \u2013 typically default.)\n<ul class=\"wp-block-list\">\n<li>DevLake itself uses an\u00a0<code>ENCRYPTION_SECRET<\/code>\u00a0key to encrypt sensitive fields in its database, such as personal access tokens and passwords for the integrations. You must configure and\u00a0safeguard this encryption key. Losing it will prevent DevLake from decrypting stored credentials, and if it were leaked, an attacker with database access could decrypt those credentials.<\/li>\n\n\n\n<li>Also enforce\u00a0encryption in transit: configure DevLake\u2019s database connection with TLS, and similarly secure Grafana\u2019s connection to the database if it\u2019s separate.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Vulnerability Management:\u00a0As an open-source project, DevLake should be kept up-to-date. Monitor Apache DevLake releases for security patches or updates. Periodically run container vulnerability scans (for instance, using Trivy) on the DevLake Docker images to catch known issues (one user reported\u00a0\u201ca long list of high and critical vulnerabilities\u201d\u00a0when scanning DevLake v1.0.1 images). Applying updates promptly and following hardening best practices (e.g., using minimal privilege containers) will help meet SOC 2 change management and system integrity requirements.<\/li>\n\n\n\n<li>Logging &amp; Monitoring:\u00a0Ensure that DevLake\u2019s operations and access are logged. While DevLake itself doesn\u2019t have a built-in audit log for user activities, you can rely on surrounding logs:\n<ul class=\"wp-block-list\">\n<li>Enable logging for DevLake\u2019s processes (it will log pipeline task events, errors, etc. to files or console) and collect those with Azure Monitor or a SIEM.<\/li>\n\n\n\n<li>Grafana will log user access to dashboards; integrate those logs to monitor who is viewing data.<\/li>\n\n\n\n<li>Monitor Azure network logs or container logs for any suspicious access patterns. Regular review of these logs and alerting on anomalies (failed login attempts, unusual data export) help satisfy SOC 2 monitoring and incident detection controls.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Availability &amp; Backup:\u00a0(While availability is a separate concern, it\u2019s often included in a PIA and SOC 2\u2019s\u00a0Availability\u00a0trust criteria.) Host DevLake in a reliable way: for example, use Azure managed database services with backups, and consider running DevLake in a cluster or with restart policies so that a single VM failure doesn\u2019t cause prolonged downtime. Back up the DevLake database periodically (the historical metrics data) to prevent loss. This ensures that the DevOps metrics are available when needed and supports continuity (important for internal users relying on these analytics).<\/li>\n<\/ul>\n\n\n\n<p>Finally, note that Apache DevLake is a relatively new tool (an Apache incubating project). Industry feedback as of 2025 indicated it was&nbsp;not yet fully mature for large-scale production use. Thus, treat this deployment as&nbsp;internal-facing and non-critical&nbsp;initially. Exercise due diligence (thorough testing, gradual rollout) and consider DevLake as a tool primarily for internal metrics, not a public-facing or mission-critical system. In SOC 2 terms, that means classifying it appropriately (likely a lower risk system) but still applying the essential security controls described above.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Key Risks and Mitigations<\/h2>\n\n\n\n<p>For the PIA, here are the key risks associated with using DevLake internally, along with mitigation strategies:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Exposure of DevOps Data:\u00a0DevLake aggregates potentially sensitive engineering information \u2013 e.g. details of code changes, build failures, or security scan results. If the DevLake database or Grafana dashboards were accessed by unauthorized parties, it could reveal internal project details or weaknesses (for example, a SonarQube report showing code vulnerabilities).<\/li>\n<\/ul>\n\n\n\n<p>Mitigation:&nbsp;Restrict access to DevLake\u2019s data strictly to the necessary teams. Use strong authentication (e.g. SSO) and role-based access on Grafana. Keep DevLake\u2019s database in a private network, accessible only by the application. Encrypt data at rest to mitigate risk even if storage is compromised. While no customer data is at stake, protecting internal data preserves confidentiality of internal process information.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Credential Compromise:\u00a0DevLake requires API credentials (tokens\/user keys) to fetch data from Jira, Jenkins, SonarQube, and Bitbucket. These credentials, if compromised, could be used to access those tools directly, potentially impacting those systems (e.g. reading or altering data in Jira or code repos).<\/li>\n<\/ul>\n\n\n\n<p>Mitigation:&nbsp;Store all integration credentials securely within DevLake. As noted, DevLake encrypts these in the DB using an internal key \u2013 ensure that is set up correctly. Limit who can configure or view these connections (only admins via the Config UI). Use dedicated read-only service accounts or tokens with the minimum scope needed for each integration (for example, a Jira API token that can only read specific project data, a Bitbucket token that cannot push code). Also, implement a token rotation policy (change tokens periodically or if a team member with access leaves).<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Lack of Built-in Security Features:\u00a0DevLake\u2019s minimalist design means it doesn\u2019t implement user accounts, multi-tenancy, or granular permissions internally. If someone gains network access to the DevLake API, they could potentially retrieve all data (since DevLake won\u2019t individually authorize queries).<\/li>\n<\/ul>\n\n\n\n<p>Mitigation:&nbsp;Use&nbsp;compensating controls&nbsp;outside of DevLake. For example, block all access to DevLake\u2019s API except through the Config UI and Grafana (which are authenticated). Ensure the server or container running DevLake is secured (OS patches, firewall, no unnecessary services). Treat the DevLake host like a sensitive server: only admins should have login access to it. Consider placing DevLake behind an internal API gateway or using firewall rules so only Grafana and authorized sources can talk to it. Also, rely on Grafana\u2019s built-in access control to limit who can see what dashboards, if multiple teams use it.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Open-Source Software Risks:\u00a0Being open-source, DevLake might have undiscovered vulnerabilities or could introduce supply-chain risks if not vetted. There is also no commercial support guarantee.<\/li>\n<\/ul>\n\n\n\n<p>Mitigation:&nbsp;Before deployment, perform a security review of the DevLake software (scan the container, review its default configurations \u2013 many of which we did above). Keep an eye on the Apache DevLake project\u2019s issue tracker for any reported vulnerabilities or patches. Using the official Docker images and verifying signatures\/hashes is recommended. Internally, you could run DevLake in a container with restricted privileges (no root user, read-only file systems, etc., as applicable) to limit impact if something were exploited. Also, ensure your team is prepared to apply updates or fixes when they become available (treat it like any other component in your stack that needs maintenance).<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data Integrity and Quality:\u00a0(This is more of an operational risk than a security risk.) DevLake will be aggregating data from multiple sources; any misconfiguration or tampering could lead to incorrect metrics, which in turn could lead to bad decisions. For instance, if someone accidentally deletes data in the DevLake DB or if DevLake fails to import some records, your dashboards might be misleading.<\/li>\n<\/ul>\n\n\n\n<p>Mitigation:&nbsp;Establish trust but verify. Limit administrative access to the DevLake database and configuration to prevent unauthorized changes. Schedule periodic spot-checks where you compare a few metrics in DevLake against the source systems (e.g., ensure a Jira ticket count in a project matches between Jira and the DevLake dashboard). Additionally, back up the data so that if something goes wrong (corruption, user error, etc.), you can restore and correct any inconsistencies.<\/p>\n\n\n\n<p>By acknowledging and planning for these risks, you can&nbsp;operate DevLake with confidence&nbsp;inside your organization. The key is that strong security controls around DevLake will compensate for its lightweight internal security, ensuring that only the right people have access and that data remains protected.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Data Sources, Data Collected, and Risk\/Mitigation Summary<\/h2>\n\n\n\n<p>The table below summarizes the key data sources Apache DevLake will integrate with, the types of data it&nbsp;collects&nbsp;from each, and the specific security&nbsp;risks&nbsp;and&nbsp;mitigations&nbsp;for each integration:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><td>Data Source<\/td><td>Data Collected by DevLake<\/td><td>Associated Security Risks<\/td><td>Recommended Mitigations<\/td><\/tr><\/thead><tbody><tr><td>Jenkins (CI\/CD)<\/td><td>Job and pipeline metadata (build start\/end times, statuses, durations, deployment results), build logs or summaries, and related commit IDs for each build.<\/td><td><em>Risk:<\/em>&nbsp;Exposure of pipeline details or build logs could reveal internal processes or deployment info. If an attacker obtained the Jenkins API credentials DevLake uses, they might access or alter CI\/CD jobs.<\/td><td><em>Mitigation:<\/em>&nbsp;Use a Jenkins API token with read-only scope (no job modification rights). Avoid including sensitive secrets in Jenkins build logs. Restrict network access so only the DevLake service can reach the Jenkins API endpoint. Monitor Jenkins for any unusual access patterns (which could indicate a stolen token), and rotate the token if suspicious activity is detected.<\/td><\/tr><tr><td>Jira (Issue Tracker)<\/td><td>Issue and project data: ticket IDs, titles, descriptions, statuses, assignees, comments, change logs, and time metrics (used for calculating lead times, closure rates, etc.).<\/td><td><em>Risk:<\/em>&nbsp;Jira tickets might contain sensitive internal information (e.g. feature plans, incident post-mortems). If DevLake\u2019s Jira data is exposed, it could reveal project details or problems. A compromised Jira API token could allow an attacker to read or possibly write issue data on Jira.<\/td><td><em>Mitigation:<\/em>&nbsp;Limit the Jira token\u2019s permissions to read-only for relevant projects. Treat DevLake\u2019s Jira-derived data with the same confidentiality as Jira itself (internal use only). In Grafana, implement access controls or separate dashboards if needed to ensure sensitive project data is only visible to the appropriate team. Store the Jira token encrypted in DevLake (default) and never hard-code it elsewhere. If an employee with access to the token leaves, regenerate the token (just as you would rotate credentials in Jira).<\/td><\/tr><tr><td>SonarQube (Code Quality)<\/td><td>Static code analysis results and metrics: number of code issues (bugs, vulnerabilities, code smells), code coverage percentages, hotspot detections, and file-level metrics from SonarQube scans.<\/td><td><em>Risk:<\/em>&nbsp;SonarQube findings can include security vulnerabilities or code quality gaps. If an unauthorized person accessed DevLake\u2019s database or Grafana, they might learn about weaknesses in the codebase. Also, a stolen SonarQube API token could expose all code quality results, or allow manipulation of scan data on the SonarQube server.<\/td><td><em>Mitigation:<\/em>&nbsp;Use a SonarQube token with read-only access to the necessary projects (and generated by a SonarQube admin account as recommended). Limit access to the DevLake dashboards that display security metrics to only those teams that need to know (e.g., development and security teams). Ensure SonarQube itself is secured (up-to-date and requiring auth for access). If possible, treat the code vulnerability data with higher sensitivity \u2013 for example, avoid exporting it outside the secure network or require VPN access for Grafana when viewing this data.<\/td><\/tr><tr><td>Bitbucket (Source Control)<\/td><td>Repository and code review data: commit metadata (commit hashes, authors, timestamps, commit messages), pull request details (PR titles, descriptions, statuses, reviewers), branch\/ref information, and mappings between commits and related issues (if linked via issue keys).<\/td><td><em>Risk:<\/em>&nbsp;Commit messages or PR descriptions might occasionally contain sensitive info (though they shouldn\u2019t \u2013 but e.g. a developer may mention an internal server name or a temporary credential). These data can reveal upcoming features or internal processes. If the Bitbucket API token is compromised, an attacker could read repository contents and possibly clone code. Developer identities (names\/emails in commits) could also be considered personal data requiring protection.<\/td><td><em>Mitigation:<\/em>&nbsp;Use a Bitbucket app password or OAuth token with&nbsp;read-only&nbsp;access to the specific repos needed. Ensure no tokens with write or admin scopes are used. Enforce good practices in source control (e.g., no secrets in commit messages or code) through pre-commit hooks or scans, reducing the chance that DevLake ever ingests sensitive secrets. Only surface high-level metrics on dashboards (e.g., number of PRs, throughput) rather than raw commit messages. For compliance, you can mask or abbreviate usernames in reports if necessary (though since this is an internal tool, it\u2019s usually acceptable to show commit authors). As always, keep the token encrypted and rotate it if there\u2019s any sign of compromise. Monitor Bitbucket logs for token usage anomalies (Bitbucket can often report when tokens were last used, which IP, etc.).<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>Each integration uses DevLake\u2019s plugin system to fetch data via the tools\u2019 official APIs,&nbsp;not&nbsp;by copying entire datasets or files. The scope of data collection is limited to what the APIs provide and what you configure: for example, the Jenkins plugin pulls build\/job data (but not source code), and the Bitbucket plugin pulls repository metadata and commit info (not full code contents, except diff metrics).&nbsp;No customer or financial data&nbsp;flows into DevLake during these processes \u2013 all ingested information is related to software development activities. Moreover, all data remains within your controlled Azure environment in DevLake\u2019s database and Grafana; nothing is sent to Apache or outside by default.<\/p>\n\n\n\n<p>By focusing on&nbsp;DevOps metrics and logs&nbsp;and implementing the security measures described above, the&nbsp;Project Impact Assessment&nbsp;can conclude that using Apache DevLake internally carries&nbsp;manageable risk. The tool can be deployed on your Azure infrastructure in a manner that meets your organization\u2019s security standards and&nbsp;SOC 2&nbsp;controls, provided that you follow best practices for network isolation, access control, credential management, and system monitoring. In return, DevLake will provide valuable visibility into engineering processes (deployments, development velocity, code quality trends) without exposing sensitive business or customer data, thereby delivering insights while keeping risk low and within compliance boundaries.<\/p>\n<div class=\"twttr_buttons\"><div class=\"twttr_twitter\">\n\t\t\t\t\t<a href=\"http:\/\/twitter.com\/share?text=aApache+DevLake+%E2%80%93+PIA+Synopsis+%28Security%2C+Data+Flows%2C+and+Risks%29\" class=\"twitter-share-button\" data-via=\"\" data-hashtags=\"\"  data-size=\"default\" data-url=\"https:\/\/shirishranjit.com\/blog1\/architect-principles\/aapache-devlake-pia-synopsis-security-data-flows-and-risks\"  data-related=\"\" target=\"_blank\">Tweet<\/a>\n\t\t\t\t<\/div><div class=\"twttr_followme\">\n\t\t\t\t\t\t<a href=\"https:\/\/twitter.com\/shiranjit\" class=\"twitter-follow-button\" data-size=\"default\"  data-show-screen-name=\"false\"  target=\"_blank\">Follow me<\/a>\n\t\t\t\t\t<\/div><\/div>","protected":false},"excerpt":{"rendered":"<p>DevOps Metrics Only, No Sensitive Customer Data Apache DevLake aggregates development data (e.g. code commits, build results, issue tickets) from DevOps tools for engineering analytics. No business or customer information is ingested, only technical metadata like CI\/CD logs and KPIs. &hellip; <a href=\"https:\/\/shirishranjit.com\/blog1\/architect-principles\/aapache-devlake-pia-synopsis-security-data-flows-and-risks\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":4,"featured_media":0,"parent":2688,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2792","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/pages\/2792"}],"collection":[{"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/comments?post=2792"}],"version-history":[{"count":1,"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/pages\/2792\/revisions"}],"predecessor-version":[{"id":2793,"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/pages\/2792\/revisions\/2793"}],"up":[{"embeddable":true,"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/pages\/2688"}],"wp:attachment":[{"href":"https:\/\/shirishranjit.com\/blog1\/wp-json\/wp\/v2\/media?parent=2792"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}