Identifiable communication interfaces and planned communication are some of the critical success factors to deliver a successful project. Communication interfaces need to be understood at the outset of a project as this will assist with the transition through the development phase to production. The critical points of contact should be identifiable for all who utilise them as they provide clear delineation of required communication across technology silos. Transparency of information will build effective relationships between the cross functional teams and built trust and strong collaboration.

Adopting clarity amongst existing roles and responsibilities within technology silos will improve communication between technology teams while they prepare to restructure their IT operation to introduce the new function. Representatives of the different support teams should engage in regular “open forum” meetings to ensure each team has visibility of upcoming project issues and changes in scope. Developing open lines of communications between teams will also help prepare the organisation to move the IT project into a production state, drawing on personnel across different support areas to provide a single holistic support team for the IT project.

The engagement between cross functional teams is a consistent theme in the Diaxion roundtable series. It is clear from the research gathered across these events that organisations of all sizes constantly struggle with effective team engagement in IT projects, however representatives of the SMB market have indicated that whilst engaging the team is still an issue, it is much less prevalent due to composite teams and proximity of staff.

For instance, a virtualisation service is complex and therefore has multiple components that constitute the service and equally, there are multiple specialist teams that provide expert knowledge and support to manage the components. Building a successful virtualisation platform requires input from a large number of specialised functional teams, each working on a different component or subsystem of the platform. Of course, these teams cannot work in isolation; in addition to designing their assigned components, they must also integrate their designs with those of the other components to ensure that the entire platform functions as a whole. It is critical, therefore, in planning a complex platform that project managers specify just which resources and information different teams will need from each other at particular stages of the project.

To help manage the communications aspect of such projects, we propose the following approach:

1. Identify unattended interfaces, areas where communication should be occurring but is not.

2. Look for unidentified interfaces, areas where communication is occurring but has not been planned.

To assist in implementing this approach, an alignment matrix can reveal mismatches between the communications and exchanges that are supposed to occur and those that actually do. It also demonstrates how well the project has been planned and executed. Another method of identifying the participation of roles in completing tasks or deliverables for a project is to use RACI matrix. Overall, the stated methods of understanding how communication should flow within your organisation will break down barriers and promote healthy, frequent and clear communication between your teams.

What does capacity planning look like within your organisation?

In most organisations existing capacity planning methodologies are rooted in decades of traditional physical server deployments and dedicated infrastructure. If an application server is at 50% load today, and load has historically doubled every 24 months, chances are your capacity planning methodology predicts that you have two years before you must add further capacity. While such an approach may work acceptably when dealing with dedicated, physical server instances the now widespread use of production server virtualisation limits how accurate and therefore worthwhile such predictions can be.

Further, when this approach fails, IT managers and administrators typically fall back on intuitive approaches to capacity planning – responding to reports of application slowness, or to changes in headcount, in a linear manner that does not account for the complex relationships between application performance and each layer of the infrastructure upon which the applications are hosted.

These intuitive capacity planning methodologies are at best inefficient, resulting in needless or poorly targeted infrastructure investment. At worst, they can be completely ineffective, resulting in highly approaches to infrastructure management with significant operational costs.

Virtually Unknowable

Virtualisation – along with the adoption of other shared systems, such as clustered database and web servers, hardware load balancing appliances and storage area networks – necessitate a holistic approach to capacity planning. It is no longer enough to simply understand resource utilisation on an application-by-application basis. Instead, IT managers must consider the inter-relationships between applications; when are peak periods for individual applications, which applications have peak periods which overlap, how do applications map to line-of-business functions, etc . Each additional piece of data which must be included in capacity planning calculations exponentially increases the complexity of the forecasting, increasing the likelihood for error and therefore decreasing the value of the capacity planning exercise itself.

Given this it is no wonder that in most organisations capacity planning for virtualised environments remains an ad hoc process, with virtual infrastructure administrators applying the traditional physical server cap planning methodology to ESX hosts and simply trying to manage around its shortfallings via “agility” in infrastructure procurement and deployment.

A New Approach

A new generation of tools are beginning to emerge that seek to resolve these problems. Approaches vary across vendors but we can see common themes between them:

the ability to automate application mapping, allowing analysis to incorporate relationships between servers
the ability to rationalise performance and capacity metrics from multiple infrastructure layers – typically application, database, operating system, hypervisor, network and storage
Scenario-based modelling of growth

By automating discovery and data collection and by operating across all layers of the application/infrastructure stack these tools help drive a transition from the old, intuitive capacity planning methodologies to one that is based on hard data, and therefore much better able to accurately predict capacity demands within your unique environment. And, as we will discussing in a forthcoming post, such a data-driven approach is critical to managing not just capacity forecasts but application performance as well.