Present the case for investment in streaming data processing in terms that a finance function will accept.
Building Real-Time Streaming Data Processing Systems
Practical training in streaming data processing, grounded in real cases and applied to your own operation.
📍 Tunis🗓️ 5 training days📚 4 modules🎓 Accredited certificate
5intensive training days
4scientific modules
8training sessions
32detailed points
Course Overview
Most outages involving streaming data processing are triggered by a change somebody considered routine. The documentation for the wider technology and systems delivery agenda is accurate only until the next release. Teams frequently over-invest in documenting this strand of technology and systems delivery and under-invest in testing it. It is designed for mixed groups, so that streaming data processing is examined from more than one functional angle. Comparative studies of the wider technology and systems delivery agenda across sectors find the same handful of failure points recurring. They leave able to brief senior management on the technology and systems delivery discipline in terms that support a decision. It concentrates on the parts of streaming data processing that determine outcomes and treats the rest proportionately. Participants apply the practice within technology and systems delivery to their own technical platform throughout, so the output is directly usable. It closes by agreeing the smallest change to this part of technology and systems delivery that would make a visible difference.
Expected Learning Outcomes
Document streaming data processing to the level a new engineer could operate it.
Translate policy on streaming data processing into procedures that hold up under day-to-day pressure.
Build the deployment pipeline for streaming data processing so releases are routine rather than events.
Build a concise technical standard for streaming data processing that colleagues can follow without further explanation.
Design backup and recovery for streaming data processing and prove it by restoring.
Plan capacity for streaming data processing against measured growth rather than optimism.
Who Should Attend
Vendor managers overseeing suppliers involved in streaming data processing.
Project managers delivering changes to streaming data processing.
Managers in small and medium organisations who own streaming data processing alongside other duties.
Coordinators responsible for keeping records and documentation of streaming data processing current.
Information security specialists protecting streaming data processing.
Software engineers and technical leads building streaming data processing.
Course Modules
Streaming data processing: requirements, targets and service levels
2 sessions · 8 pointsSession 1Designing streaming data processing around how it will fail
- Verify six months later that changes to streaming data processing have held.
- Set out how exceptions to streaming data processing are requested and approved.
- Set the review interval for streaming data processing and who attends.
- Identify the single points of failure in streaming data processing.
Session 2Retiring the legacy part of streaming data processing
- Configure alerting on streaming data processing that reflects what users experience.
- Review logging on streaming data processing for coverage and retention.
- Document the runbook for streaming data processing to the level a new engineer could use.
- Restore a backup of streaming data processing in a test environment and time it.
Streaming data processing: capacity, performance and load
2 sessions · 8 pointsSession 1Running an incident on streaming data processing calmly
- Decide what will be stopped to create capacity for streaming data processing.
- Assign responsibility for keeping documentation of streaming data processing current.
- Review access rights on streaming data processing and remove what is no longer needed.
- Confirm the support model and escalation path for streaming data processing.
Session 2Monitoring streaming data processing from the user's point of view
- Close out actions on streaming data processing rather than leaving them open indefinitely.
- Prepare the response for the most likely failure in streaming data processing.
- Write down the assumptions underpinning the approach to streaming data processing.
- State the availability and recovery objectives for streaming data processing as numbers.
Streaming data processing: incident response and severity
2 sessions · 8 pointsSession 1Least privilege in streaming data processing without blocking the work
- Confirm that those complying with streaming data processing understand why it exists.
- Establish the boundary of streaming data processing and record what sits outside it.
- Arrange the handover of streaming data processing so capability survives staff changes.
- Benchmark the organisation's streaming data processing against comparable operations.
Session 2The paperwork for streaming data processing that is actually needed
- Define incident severity levels for streaming data processing and the response each triggers.
- Set delivery and reliability indicators for streaming data processing the team trusts.
- Inventory third-party dependencies inside streaming data processing and their update status.
- Record the technical debt in streaming data processing and schedule repayment.
Streaming data processing: documentation, support and handover
2 sessions · 8 pointsSession 1Building lasting competence in streaming data processing
- Confirm data retention and deletion rules applied within streaming data processing.
- Agree the smallest change to streaming data processing that would be visibly useful.
- Measure current load on streaming data processing and project it forward twelve months.
- Set out the decisions in streaming data processing that require sign-off and by whom.
Session 2The hard cases in streaming data processing and how to reason about them
- Test the failover for streaming data processing rather than assuming it works.
- Confirm that reporting on streaming data processing reaches the people who can act.
- Define the trigger that would require streaming data processing to be redesigned.
- Confirm every release of streaming data processing can be rolled back within a defined time.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
USD1,850
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
We will contact you within one business day to confirm.