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Heroku Connect is a widely used service for synchronizing data between a Salesforce organization and a Heroku Postgres database [2]. For applications that rely on Salesforce data, this synchronization is a business-critical function. However, while Heroku Connect is great for getting data flowing, it often falls short when it comes to providing the comprehensive monitoring and observability teams need. This gap can lead to significant problems, including silent sync failures, frustrating data discrepancies, and hours of manual troubleshooting, putting data integrity at risk.
Achieving complete Heroku Connect monitoring and observability is challenging due to several inherent limitations in the platform's design. These challenges force teams into a reactive, rather than proactive, stance on data integrity.
Heroku Connect’s native monitoring capabilities are basic. The Heroku Connect Dashboard provides a high-level overview, allowing you to view logs and manage data mappings, but it lacks the depth needed for true observability [3]. You can see if a sync is active or has an error, but you can't get real-time, granular insights into performance, data flow, or potential bottlenecks. This makes it incredibly difficult to spot issues before they become critical problems.
When a problem does arise, troubleshooting in Heroku Connect is often a reactive and manual process. Developers must follow a series of diagnostic steps to even begin to understand the root cause [4]. Common issues, like slow sync performance, require tedious investigation and analysis of logs to figure out why writes to Salesforce are lagging [8]. This manual effort consumes valuable engineering time that could be spent on building features.
Perhaps the most dangerous challenge is the risk of "silent sync failures," where data synchronization stops or becomes inconsistent without triggering any clear, immediate alerts. For example, a sync might halt unexpectedly if it hits the maximum number of duplicate updates allowed in a single batch, a subtle error that is difficult to catch [7]. These observability gaps can lead to severe data integrity issues, where business decisions are made based on outdated or incomplete information.
For teams that need more than what Heroku Connect offers, Stacksync provides a dedicated data sync and observability platform designed to overcome these limitations. Instead of a "black box," Stacksync delivers a complete, end-to-end view of your data pipelines, giving you the visibility and control needed to ensure data integrity. Heroku Connect’s limited observability is easily solved with Stacksync, turning a major operational risk into a manageable, transparent process.
Stacksync features a real-time monitoring dashboard that offers live insights into sync status, data volume, and overall performance. Unlike the basic logs in Heroku, the Log Explorer in Stacksync allows teams to search, filter, and analyze execution logs at scale. This means you can trace the lifecycle of a single record or query for specific errors across millions of events in seconds, making root cause analysis faster and more efficient.
The Issue Management dashboard in Stacksync is designed to prevent silent failures by centralizing every sync error in one place. You can configure real-time alerts via Slack, email, or other notification channels to be notified the moment an issue occurs. Better yet, Stacksync allows you to fix Heroku Connect conflict errors and other issues by retrying or reverting failed syncs in a single click, dramatically reducing mean time to resolution (MTTR).
Stacksync’s Smart API Rate Limits feature helps you avoid hitting Salesforce API quotas by automatically managing request traffic. This prevents syncs from failing due to rate limiting, a common issue with high-volume data flows. Stacksync is architected from the ground up to handle massive datasets without the performance bottlenecks often seen with other tools, which is why high-volume Heroku Connect fails and Stacksync wins for enterprise-scale workloads.
When you compare the two platforms side-by-side, the difference in observability becomes clear. Stacksync is not just another sync tool; it's an enterprise-grade platform built for reliability and transparency. For businesses looking to replace Heroku Connect with an affordable real-time sync that scales, the advantages are compelling.
Getting started with Stacksync is a straightforward process that doesn't require months of development. You can have full observability up and running in a few simple steps.
First, sign up for a Stacksync account and create a new project. The platform offers a 14-day free trial, allowing you to test its full capabilities without commitment.
Using a simple no-code interface, connect your Salesforce organization and your Heroku Postgres database to the Stacksync platform. Stacksync uses secure authentication methods like OAuth 2.0 to ensure your data is protected.
Once connected, you can easily map objects and fields between Salesforce and Postgres. Stacksync automatically suggests mappings and allows you to beat Heroku Connect object sync limits by supporting an unlimited number of standard and custom objects.
With your sync configured, you can immediately navigate to the monitoring dashboard to track data flows in real-time. Set up alerts for specific error types or performance thresholds to be notified of any deviation, and start using the Log Explorer to gain deep insights into your sync health.
While Heroku Connect offers a functional way to sync data, its lack of robust observability creates significant risks for any business that relies on timely and accurate information. The inability to proactively monitor syncs, receive real-time alerts, and quickly resolve issues leaves engineering teams in a constant state of reaction.
Stacksync fills this critical gap by providing the real-time monitoring, proactive alerting, and advanced issue management needed for true enterprise-grade data synchronization. By empowering your teams with full visibility, you can prevent data issues before they impact the business and move from reactive firefighting to proactive, strategic data management.
