Heroku Goes “Sustaining Engineering”: What It Signals for RevOps Stacks (and How to De-Risk Your CRM Automations)

Heroku moving into “sustaining engineering” is not just a platform update. It is a signal about where Salesforce wants customers to place new build energy in 2026, and it changes the risk profile for any RevOps stack that quietly depends on Heroku apps to keep revenue moving.

Salesforce’s own update (Feb 6, 2026) says Heroku is transitioning to a sustaining engineering model focused on “stability, security, reliability, and support,” with “no change” to day-to-day usage for current customers, while new Enterprise Account contracts will no longer be offered. That is a crisp, explicit shift in roadmap posture. (Heroku blog)

TL;DR

• “Salesforce Heroku sustaining engineering” means Heroku remains supported, but you should assume slower innovation, fewer ecosystem changes, and higher long-term roadmap risk.
• If your GTM motion relies on custom Heroku apps for lead routing, enrichment, sequencing triggers, and data sync, your biggest risk is not “downtime”, it is silent failure and “works, but wrong” automation outcomes.
• In 2026, the safer default is: move critical revenue logic closer to the system-of-record (CRM, engagement platform, data warehouse) and use custom apps for differentiated workflows only.
• You can stabilize in 30 days with an inventory, SPOF mapping, monitoring, and a staged migration of the top 3 revenue-critical workflows into AI-native CRM features (scoring, enrichment, agent-driven routing) where possible.

What Heroku’s shift actually says (and why RevOps should care)

Salesforce confirmed Heroku is now focused on sustaining engineering: stability, security, reliability, support, with core functionality unaffected for existing customers. It also states that new enterprise contracts are no longer offered. (Heroku blog)

Third-party coverage framed this as Salesforce halting development of new features for Heroku and moving it into sustaining engineering, while renewals continue for existing customers. (TechRadar, Salesforce Ben)

For RevOps, the key takeaway is not “Heroku is going away tomorrow.” The takeaway is:

• Your Heroku-based GTM logic has a longer tail of operational support, but a shorter tail of strategic investment.
• Over time, that tends to increase integration friction, dependency risk, and talent risk (harder to justify improving and expanding custom systems).

If your sales workflow relies on a Heroku app, you are now effectively operating a piece of your revenue engine on a platform that Salesforce is publicly positioning as “maintain, not evolve.”

What “sustaining engineering” typically means in practice

“Sustaining engineering” is commonly used to describe engineering work that maintains an existing system, reduces ownership cost, and improves readiness and reliability rather than expanding capabilities. (DLA definition, Law Insider definition)

In software terms, for an operator (you), it usually implies four things:

1) Roadmap risk goes up

You may still get:

• Security patches
• Reliability improvements
• Compliance maintenance that is required to keep the service viable

You are less likely to get:

• New platform primitives
• Major UX or developer experience upgrades
• Big ecosystem moves (new add-on classes, deep native integrations, etc.)

2) Security-only does not mean “no risk”

Security patches help, but RevOps risk is often business logic drift:

• Your CRM changes, objects change, field names change, event payloads change.
• Your outbound tool changes webhooks, rate limits, auth scopes.
• Your enrichment vendors change endpoints, pricing, or data fields.

A sustaining-mode platform can remain secure and stable while your surrounding ecosystem changes faster than your integration layer can.

3) Slower ecosystem change increases “glue code” burden

If you rely on Heroku as your integration hub, you are likely running:

• Scheduled jobs
• Queue workers
• Webhook listeners
• Custom middleware logic

When the surrounding stack evolves, you end up writing more code to keep parity.

4) More “supply chain” events (stack and dependency pressure)

Even without new features, platform lifecycle still moves. Example: Heroku-20 (Ubuntu 20.04-based stack) reached end-of-life on April 30, 2025, with a clear schedule where builds eventually stop being supported. (Heroku Help)

This matters to RevOps because build pipelines, security patches, and dependency upgrades often get deferred on “internal tools.” Those tools frequently include your revenue-critical automations.

Reliability is not theoretical: outages happen, and status channels change

Two operational signals to treat as “stack risk multipliers”:

Heroku has had major incidents that affected customer operations

Heroku published a corrective action update for the June 10, 2025 outage, including the detail that the Heroku status site itself was affected and appeared to show no active incidents due to shortcomings and latency/timeouts. (Heroku blog)

You can also see downstream customer reports tying their outages to Heroku issues on that date. (Torchbox status, Cyberday post)

Incident communications are shifting to Salesforce Trust

As of Oct 10, 2025, Salesforce Trust is the primary channel for Heroku incident and maintenance communications, with the old status site remaining as a parallel backup for now. (Heroku Dev Center, Heroku Dev Center status article)

For RevOps teams, this is a cue to:

• Make sure the right people are subscribed to the right channel.
• Ensure your monitoring is not dependent on one brittle status integration.

Where RevOps teams are most over-dependent on custom Heroku apps

Most GTM teams do not “choose Heroku for RevOps.” They inherit it:

• A sales engineer built a routing service.
• Growth built a webhook receiver to fan out to tools.
• RevOps added enrichment scripts because “it was faster than procurement.”
• A consultant delivered a custom scoring model tied to CRM events.

Here are the most common Heroku-hosted revenue workflows that become risky in sustaining mode:

Lead routing and assignment (highest blast radius)

Symptoms of failure:

• Leads pile up unassigned
• Hot leads get routed to the wrong segment
• Round-robin breaks, territory rules drift
• SLAs quietly die

Common Heroku patterns:

• Webhook from form fill or product signup
• Router service applies rules, writes to CRM
• Notification job pings Slack or sequences an SDR

Enrichment jobs (silent data quality failures)

Symptoms of failure:

• Higher bounce rates
• Poor personalization
• Lead scoring degrades
• Segments become unreliable

If you are doing “waterfall enrichment” with multiple vendors and logic, this tends to live in custom code because it started as “just a script.”

Outbound sequencing triggers (high compliance and reputation risk)

Symptoms of failure:

• Prospects get sequenced without proper consent logic
• Suppression lists do not apply
• Unsubscribes fail to propagate
• You keep sending after a hard bounce

This area is especially risky because the failure mode is often “still sending” rather than “stopped.”

If you run high volume outbound, pair this with a weekly deliverability governance routine. (Internal: Cold Email Deliverability Engineering: SPF, DKIM, DMARC, List-Unsubscribe, and Monitoring (2026 Setup Guide), and Email Deliverability Governance Dashboard (2026): A Weekly Scorecard Template)

Sync middleware between CRM, product, and data warehouse (slow-burn risk)

Symptoms of failure:

• Duplicate records
• Timestamp drift and wrong “last touch”
• Missing lifecycle stage transitions
• Reports stop matching source systems

The cost is not just bugs. It is executive trust.

Decision framework (2026): build vs buy when Heroku is in sustaining engineering

If you are deciding what to keep on Heroku vs what to migrate, use a simple scoring rubric. In 2026, build is still valid, but it must be reserved for the right work.

Step 1: classify the workflow by “revenue criticality”

Use three tiers:

1. Tier 1 (Revenue-critical, real-time):

   • Lead routing
   • Dedup + identity resolution used for outreach
   • Suppression and consent enforcement
   • Payment or contract triggers that change sales motion

2. Tier 2 (Revenue-impacting, near-real-time):

   • Enrichment
   • Scoring
   • Segmentation
   • Sales alerts and task creation

3. Tier 3 (Operational convenience):

   • Slack summaries
   • Weekly rollups
   • Nice-to-have dashboards
   • Non-critical automations

Rule: Tier 1 should default to buy or native, unless you have a strong reason.

Step 2: score “change velocity” around the workflow

Ask:

• How often do upstream APIs change?
• How often do your ICP rules change?
• How often do territories change?
• How often do you swap vendors?

High change velocity favors buy or native features.

Step 3: test “explainability” and “auditability” requirements

If you cannot answer “why did this lead get routed here?” in 60 seconds, you have a governance problem.

This is where AI-native CRMs can help, but only if they provide:

• Audit trails
• Rule visibility
• Replayable decisions
• Approval workflows

Internal: CRM Evaluation Rubric for 2026: Data Governance, Audit Trails, and Agent Guardrails, and Agentic CRM Workflows in 2026: Audit Trails, Approvals, and “Why This Happened” Logs

Step 4: decide “where the source of truth lives”

A stable architecture usually looks like:

• CRM: canonical owner of accounts, contacts, opportunities, lifecycle stages
• Warehouse: canonical owner of analytics and historical events
• Engagement platform: canonical owner of messaging events and compliance artifacts
• Custom apps: only for differentiated logic, not for glue

If Heroku apps are currently the “truth” for routing rules or enrichment results, migrate that ownership.

De-risk checklist: stabilize Heroku-based CRM automations now

Use this as a practical checklist you can run this week.

1) Inventory every automation (and label owners)

Create one sheet with columns:

• Automation name
• Trigger (webhook, schedule, manual)
• Input systems (CRM, forms, product, billing, data vendor)
• Output systems (CRM fields, sequences, Slack, warehouse)
• Frequency and SLA (real-time, hourly, daily)
• Owner (person, not team)
• On-call path (who gets paged)
• Last time tested end-to-end

Deliverable: an automation registry. No registry, no governance.

2) Identify single points of failure (SPOFs)

Mark any workflow as SPOF if:

• Only one dyno/worker handles it
• Only one API key exists and it is long-lived
• Only one engineer understands it
• No replay queue exists
• Failures are logged but not alerted

Pay extra attention to:

• Lead routing
• Enrichment pipelines
• Outbound sequencing triggers
• Dedup/merge logic

3) Add monitoring and alerting that detects “wrong outcomes”

Most teams monitor uptime. You need to monitor business invariants.

Examples of invariants (simple, powerful):

• “Unassigned inbound leads > X for Y minutes”
• “% leads missing phone/email > threshold”
• “Enrichment job success rate < 95%”
• “Route-to-first-touch SLA p95 > target”
• “Sequence enrollments from source = product signup should be within expected range”

If you want metrics that correlate to pipeline, track them weekly. Internal: Outbound Ops Metrics That Actually Predict Pipeline: 12 Numbers to Track Weekly (With Targets)

4) Build a replay and backfill mechanism

For each Tier 1 and Tier 2 workflow:

• Store incoming events (queue or durable log)
• Make processing idempotent (safe to replay)
• Implement backfill scripts for last 7, 30, 90 days
• Log a correlation ID into the CRM record for audit

This is how you recover from “we were down for two hours” without losing revenue.

5) Move critical workflows into AI-native CRM features where possible

This is not about chasing “AI.” It is about reducing custom surface area.

Candidates to migrate first:

• Scoring: dynamic lead scoring and prioritization
• Routing: agent-assisted routing with guardrails, plus human approval for edge cases
• Enrichment: multi-source enrichment that is monitored and tied to outbound outcomes

Internal: Dynamic Lead Scoring in 2026: The Model, the Signals, and the Playbook, and Waterfall Enrichment in 2026: How Multi-Source Data Cuts Bounces and Increases Reply Rates

If you keep custom logic, keep it thin: transform, validate, route. Do not let it become the brain of your GTM.

30-day stabilization plan (for teams running GTM logic on Heroku)

This is designed for RevOps leaders who need a fast, low-drama path that does not require a full platform migration in month one.

Days 1-7: map and stop the bleeding

1. Create the automation registry (inventory).
2. Rank workflows by:
   • Revenue criticality (Tier 1-3)
   • Failure frequency
   • Time-to-detect today
   • Time-to-recover today
3. For the top 5 workflows, implement:
   • Error alerts to Slack + email
   • Basic SLO dashboards (success rate, latency, backlog)
4. Subscribe the right team to the correct incident channel(s) and ensure escalation paths are clear, since Salesforce Trust is now the primary channel for Heroku incidents. (Heroku Dev Center)

Days 8-15: eliminate silent failure

1. Add business invariant checks (unassigned leads, missing enrichment, routing SLA).
2. Add dead letter queues or “failed event tables.”
3. Implement replay for at least Tier 1 workflows.
4. Run a tabletop exercise:
   • “Heroku app is up but CRM writes fail”
   • “Enrichment vendor rate-limits”
   • “Webhook schema changes”

Days 16-23: reduce dependency on Heroku for the most critical logic

1. Pick the top 1 Tier 1 workflow (usually routing).
2. Decide target state:
   • Native CRM routing rules + approvals, or
   • AI agent routing with explainable logs, or
   • Dedicated routing service outside Heroku (if you must keep custom)
3. Implement a parallel run:
   • Old Heroku logic continues
   • New path runs in “shadow mode”
   • Compare outputs daily

Days 24-30: formalize governance and lock in operational excellence

1. Define:
   • Owners and SLAs per workflow
   • On-call rotation rules
   • Change management (who can deploy, who can edit routing)
2. Add a weekly RevOps “automation review”:
   • Top failures
   • Drift in outcomes
   • Vendor/API changes
   • Backlog of migrations from Tier 1 custom to native/buy

If you do outbound at scale, include deliverability governance in the same weekly cadence so automation errors do not become reputation damage. Internal: Instantly Hypersend Mode and the Rise of Extreme-Scale Outbound

FAQ

What does “Salesforce Heroku sustaining engineering” mean for existing customers?

It means Heroku remains supported and production-ready, with emphasis on stability, security, reliability, and support, but Salesforce is not positioning Heroku for new feature investment in the same way. Salesforce also stated new Enterprise Account contracts will no longer be offered, while existing enterprise subscriptions can renew. (Heroku update)

Should RevOps teams migrate off Heroku immediately?

Not automatically. The right move is to migrate or redesign the workflows where Heroku is a single point of failure for revenue, especially lead routing, suppression/consent logic, and sequencing triggers. Keep lower-tier jobs on Heroku short term if they are well monitored and replayable.

What is the biggest hidden risk of running GTM automations on Heroku?

Silent failure and “wrong outcomes.” A routing service can be up while API writes fail, tokens expire, schemas drift, or rate limits kick in. That can quietly misroute leads, skip enrichment, or enroll the wrong prospects into sequences.

How do I know if a workflow should be built or bought in 2026?

Default to buy or native if the workflow is Tier 1 revenue-critical, changes frequently, or requires strong auditability and governance. Build custom only when it is a durable differentiator and you can support monitoring, replay, and ownership long term.

What monitoring should I add first?

Start with business outcome alerts, not uptime:

• Unassigned inbound leads
• Route-to-first-touch SLA
• Enrichment coverage rate
• Sequence enrollment anomalies
• Error budgets for API write failures
  Then add replay queues and correlation IDs for auditability.

Start the 30-day Heroku-to-RevOps stabilization sprint

1. Assign a single DRI for the automation registry and SPOF mapping.
2. Identify your top 3 revenue-critical Heroku workflows and implement monitoring + replay.
3. Move one Tier 1 workflow (usually routing or scoring) into AI-native CRM functionality or a bought tool with audit trails.
4. Set a weekly governance routine: outcomes, failures, drift, and vendor change review.