- Industry: Telecommunication
- Geography: New Zealand
- Data Scale: Multiple Apache NiFi clusters deployed across Dev, QA, and Production, collectively orchestrating hundreds of continuous, real-time data pipelines.
- Real-time ingestion of network and device events.
- Processing of subscriber usage and billing-related data.
- Streaming data feeds for analytics, monitoring, and fraud detection.
- Movement of regulatory and compliance data across internal systems.
Any Apache NiFi serves as the backbone of the customer’s real-time data platform, powering:
Any disruption in NiFi directly impacts service reliability, reporting accuracy, and regulatory confidence, making operational stability and control non-negotiable.
- As NiFi scaled, manual and inconsistent deployments increased operational risk.
- Upgrades were risky and frequently postponed, leading to platform drift.
- Lack of centralized governance and change control across Dev, QA, and Production.
- A rising number of production incidents caused by misconfigurations.
- Heavy reliance on senior NiFi engineers for routine deployments and fixes.
The telecom provider adopted open-source Apache NiFi to reduce ETL licensing costs.
Operational effort continued to grow, offsetting the cost benefits of open source.
|
Operational Metrics
|
Before DFM
|
|---|---|
|
Deployment time per flow
|
3–4 hours
|
|
Failed deployments
|
15-20%
|
|
Rollback capability
|
Manual, risky
|
|
Engineering effort
|
2-3 engineers, full-time
|
|
Audit readiness
|
Manual, fragmented
|
As the platform grew, the lack of deployment discipline and visibility directly impacted release velocity, stability, and compliance readiness.
- Retained the flexibility and open-source nature of Apache NiFi without forcing a platform change.
- Replaced manual, error-prone flow deployments with automated and repeatable processes.
- Introduced governance and audit trails required for regulated telecom environments.
- Enabled predictable releases and rollbacks, reducing fear around production changes.
- Improved cost visibility and operational efficiency without introducing vendor lock-in.
The customer had already invested heavily in Apache NiFi and trusted it for mission-critical data flows. Replacing NiFi was neither practical nor desirable. What they needed was a way to operate NiFi like an enterprise platform, safely, predictably, and at scale.
Data Flow Manager (DFM) was chosen because it addressed the day-to-day operational pain of running NiFi in production:
In effect, DFM allowed the team to keep NiFi as their data engine while adding the control plane it was missing.
The implementation of Data Flow Manager (DFM) was focused on bringing consistency, control, and confidence to NiFi operations across teams and environments:
- Onboarded multiple NiFi clusters into a single control layer.
- Centralized management of Dev, QA, and Production environments.
- Standardized the end-to-end flow lifecycle, from development to production.
- Introduced approval-based flow deployments with clear role separation.
- Automated flow sanity and validation checks before production release.
- Enabled scheduled flow deployments to reduce release-day risk.
- Established controlled NiFi upgrade orchestration to avoid last-minute surprises.
The rollout was incremental and non-disruptive, allowing teams to adopt DFM quickly while immediately reducing operational risk.
| Metrics | Before DFM | After DFM |
|---|---|---|
| Deployment time | 3–4 hours | 20–30 minutes |
| Failed deployments | Frequent | Near zero |
| Monthly ops effort | High | Reduced by ~70% |
| NiFi upgrades | Risky / avoided | Controlled & repeatable |
| Audit readiness | Manual | One-click |
With DFM in place, the telecom provider achieved:
- Faster time-to-market for new data pipelines.
- Significant reduction in production incidents.
- Lower dependency on senior NiFi specialists.
- Predictable, scheduled release cycles.
- Increased confidence and trust in the data platform.
Operations shifted from reactive firefighting to proactive platform governance.
“DFM fundamentally changed how we manage Apache NiFi. Deployments are faster, safer, and fully auditable, giving our team confidence to scale NiFi across the enterprise.”
— Platform Engineering Lead, Telecom (New Zealand)
- Telecom operators running NiFi at scale.
- Enterprises migrating from proprietary ETL tools.
- Platform teams supporting multiple environments.
- Regulated industries requiring auditability and governance.
If NiFi is becoming mission-critical in your organization, operational control is no longer optional.
See how DFM can Reduce Your NiFi Operational Effort by up to 70%