You can reply warmly but professionally like this:
Thanks Murali, appreciate your support.
Likewise, I am also learning and catching up as we move across Oracle, PostgreSQL on-prem, Azure, and now Emerging DB topics. Since our paths have crossed across these areas, I’m happy to share whatever context I have and keep things aligned wherever possible.
Thanks again.
Before progressing RFC14049525, can we please revalidate the actual requirement and DBA ownership?
This appears to be related to synonym execution/creation, which is normally an application object activity and not something DBA should execute in this environment unless there is a formally agreed exception.
Also, before assigning such RFCs to DBAs, especially over the weekend, please ensure the requirement is reviewed properly and the DBA scope is clear.
Thanks.
Hi Ajinkya,
Thanks for highlighting this.
We are aware of the AMR capacity situation across the mentioned Azure regions. Microsoft has also acknowledged the concern in our recent discussion, and we are awaiting their detailed plan/next steps.
In the meantime, could you please confirm if the suggested mitigation options have been tried from your side, such as retrying the provisioning, trying during off-peak hours, checking alternate SKU options, or validating if another region can be used where workload requirements allow?
Once we receive further guidance from Microsoft, we will share the update accordingly.
Regards,
Nikhil
Please summarize this meeting as a structured Q3 cost-optimization alignment note for Emerging DB.
Include:
Keep the summary concise, professional, and suitable to share with the team after the meeting.
Do we have cost visibility around this
Are queries consuming high RUs due to poor filters or cross-partition scans?
Review oversized Redis/AMR instances.
Review Mongo vCore cluster sizing and usage patterns to ensure compute, storage, backup, and environment configuration are aligned with actual workload needs.
Do we have idle or rarely used clusters?
Is storage growing due to unused or test data?
Are diagnostic settings consistent across products?
Review diagnostic logging, metrics, and retention configuration to avoid unnecessary monitoring cost .
uncontrolled logging becomes expensive.
Do any Emerging DB non-prod resources support scheduled scale-down or reduced capacity during non-business hours?”
Objective: Review whether Cosmos containers are indexing all fields unnecessarily.
Why it matters: excessive indexing can increase RU consumption during writes.
“Can we review if Cosmos indexing policies are optimized, especially for containers with heavy write activity?”
Can we review memory utilization versus allocated SKU for Redis/AMR and identify right-sizing opportunities?”
Policy expiration review
Where we allow high SKU, HA, autoscale, persistence, or geo-replication by exception, can we add review/expiry so exceptions don’t stay forever?
Can we define standard lower-environment templates for Cosmos, vCore, and AMR so teams don’t accidentally provision production-like configurations?
Hi Team, thanks for joining.
The purpose of this call is to align on possible cost-optimization opportunities for Emerging DB and see what can be considered for Q3 objectives.
We are not trying to finalize everything today, but we should identify potential areas, understand feasibility, impact, effort, and any dependencies.
I’ll first request [PO Name] to share the expectation/business objective, and then we can go through inputs from the engineering side.
-
Ask PO:
“[PO Name], could you please share what outcome you are expecting from the cost-optimization objective for Q3?”
Also ask:
“Are we focusing mainly on lower environment cost, unused resources, SKU optimization, policy controls, or overall product cost?”
2. Ask engineers for ideas
Say:
“From engineering side, let’s discuss where we see cost-saving opportunities.”
Prompt them with examples:
“Do we see opportunities around SKU downgrade, autoscale restriction, HA/geo-replica restriction, persistence removal, unused resources, policy controls, or migration from higher-cost services?”
3. For each idea, ask these questions
“What is the current cost concern?”
“Which product and environment is impacted?”
“What change are we proposing?”
“What is the expected saving or benefit?”
“Any risk or user impact?”
“Is this policy, configuration change, analysis, or implementation?”
“Can this be taken in Q3, or does it need more refinement?”
4. Categorize items during the call
Use simple buckets:
“Let’s classify this as: Ready for Q3, Needs Analysis, Dependency/Blocked, or Parked.”
5. Close the call
Say:
“Thanks Team. I’ll summarize the discussed cost-optimization ideas with product, impact, feasibility, owner/context, and next step. For valid Q3 candidates, we can create or refine GitLab items and align with PO for priority.”
##
Alright , I will come to ___ next
Alright, moving on to the next topic
Got it, I’ll capture that. Any other input before we move to the next item?
Clear, we’ll proceed with that direction
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