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The One Thing Destroying Office 365 Deployments - and How to Fix It - Part 1

Wilfried van Haeren

Market exuberance for Office 365 has inspired business mandates to adopt the cloud-hosted collaboration and productivity suite without regards to the underlying chaos. While multi-location organizations are virtualizing, operating models haven’t necessarily changed. This partial transformation that excludes automation and simplification of the network puts Office 365 deployments (and other software-as-a-service offerings) in danger of failing.

Take banking as an example — IT must design an architecture that can support the varying needs of thousands of branch locations and multiple divisions. Where the consumers at the branches might require online banking and informational video streaming, the trading division (a much smaller subset of the organization that typically makes the bulk of the revenue) will need their applications prioritized.

To achieve this, IT may start to build an overlay network, relaying this blend of application services across the plain old data network and continuing to rely on backhauling. In these situations, when a customer wants to complete a large money transfer or open an account, the data packets of this application may cross an entire continent before going back to a cloud provisioning center that is next-door. Unnecessary travel isn’t just inefficient in cost, bandwidth, and response time — it’s where chaos is born, and impacts application performance and end-user response time through increased latency during transfer.

Chaos Takes Many Forms, But Always Creates the Same Challenges

Chaos isn’t limited to backhauling or using generic devices to route traffic. Instead, it can include:

■ Stacking physical hardware appliances with different network functions in an attempt to enforce business policies at the branch edge of the network

■ Running a separate infrastructure for important business functions

■ Using connectivity that was chosen based on price, rather than performance and agility

■ A network platform lacking orchestration or automation capabilities

Regardless of the exact network configuration, chaos consistently creates the following challenges when attempting to deploy Office 365:

Poor Performance and End-User Experience - Long and inefficient traffic patterns add latency and diminish the user experience. Additionally, without any orchestration or automation there is no distinction between transactional or bulk application types for appropriate performance and availability controls.

Increased Costs - While on the surface, replacing legacy desktop applications appears to be a cost reduction, deploying Office 365 on existing architecture without fine-grained application policy and bandwidth controls leads to increasing connectivity costs to manage the application demands.

Diminished Visibility - The complexity of chaos can lead to confusion or clouding of current bandwidth usage, unimportant traffic traveling across an expensive MPLS connection, and overprovisioning to combat poor performance that is unrelated to bandwidth.

Read The One Thing Destroying Office 365 Deployments - and How to Fix It - Part 2, covering how SD-WAN tames Office 365 chaos.

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The One Thing Destroying Office 365 Deployments - and How to Fix It - Part 1

Wilfried van Haeren

Market exuberance for Office 365 has inspired business mandates to adopt the cloud-hosted collaboration and productivity suite without regards to the underlying chaos. While multi-location organizations are virtualizing, operating models haven’t necessarily changed. This partial transformation that excludes automation and simplification of the network puts Office 365 deployments (and other software-as-a-service offerings) in danger of failing.

Take banking as an example — IT must design an architecture that can support the varying needs of thousands of branch locations and multiple divisions. Where the consumers at the branches might require online banking and informational video streaming, the trading division (a much smaller subset of the organization that typically makes the bulk of the revenue) will need their applications prioritized.

To achieve this, IT may start to build an overlay network, relaying this blend of application services across the plain old data network and continuing to rely on backhauling. In these situations, when a customer wants to complete a large money transfer or open an account, the data packets of this application may cross an entire continent before going back to a cloud provisioning center that is next-door. Unnecessary travel isn’t just inefficient in cost, bandwidth, and response time — it’s where chaos is born, and impacts application performance and end-user response time through increased latency during transfer.

Chaos Takes Many Forms, But Always Creates the Same Challenges

Chaos isn’t limited to backhauling or using generic devices to route traffic. Instead, it can include:

■ Stacking physical hardware appliances with different network functions in an attempt to enforce business policies at the branch edge of the network

■ Running a separate infrastructure for important business functions

■ Using connectivity that was chosen based on price, rather than performance and agility

■ A network platform lacking orchestration or automation capabilities

Regardless of the exact network configuration, chaos consistently creates the following challenges when attempting to deploy Office 365:

Poor Performance and End-User Experience - Long and inefficient traffic patterns add latency and diminish the user experience. Additionally, without any orchestration or automation there is no distinction between transactional or bulk application types for appropriate performance and availability controls.

Increased Costs - While on the surface, replacing legacy desktop applications appears to be a cost reduction, deploying Office 365 on existing architecture without fine-grained application policy and bandwidth controls leads to increasing connectivity costs to manage the application demands.

Diminished Visibility - The complexity of chaos can lead to confusion or clouding of current bandwidth usage, unimportant traffic traveling across an expensive MPLS connection, and overprovisioning to combat poor performance that is unrelated to bandwidth.

Read The One Thing Destroying Office 365 Deployments - and How to Fix It - Part 2, covering how SD-WAN tames Office 365 chaos.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...