Activity-Based Scheduling of IT Changes

Transcription

1 Aciviy-Based Scheduling of IT Changes David Trasour, Maher Rahmoun Claudio Barolini Trused Sysems Laboraory HP Laboraories Brisol HPL July 3, 2007* ITIL, change managemen, scheduling Change managemen is a disciplined process for inroducing required changes ono he IT environmen, wih he underlying objecive of minimizing disrupions o he business services as a resul of performing IT changes. Currenly, one of he mos pressing problems in change managemen is he scheduling and planning of changes. Building on an earlier mahemaical formulaion of he change scheduling problem, in his paper we ake he formulaion of he problem one sep furher by breaking down he changes ino he aciviies ha compose hem. We illusrae he heoreical viabiliy of he approach, discuss he limi of is applicabiliy o real life scenarios, describe heurisic echniques ha promise o bridge he scalabiliy gap and provide experimenal validaion for hem. * Inernal Accession Dae Only AIMS 2007, LNCS 4543, pp , 2007 Copyrigh 2007 Springer-Verlag Berlin Heidelberg Approved for Exernal Publicaion

2 Aciviy-Based Scheduling of IT Changes David Trasour, Maher Rahmouni, and Claudio Barolini 2 HP Labs Brisol, UK 2 HP Labs Palo Alo, USA {david.rasour,maher.rahmounclaudio.barolini}@hp.com Absrac. Change managemen is a disciplined process for inroducing required changes ono he IT environmen, wih he underlying objecive of minimizing disrupions o he business services as a resul of performing IT changes. Currenly, one of he mos pressing problems in change managemen is he scheduling and planning of changes. Building on an earlier mahemaical formulaion of he change scheduling problem, in his paper we ake he formulaion of he problem one sep furher by breaking down he changes ino he aciviies ha compose hem. We illusrae he heoreical viabiliy of he approach, discuss he limi of is applicabiliy o real life scenarios, describe heurisic echniques ha promise o bridge he scalabiliy gap and provide experimenal validaion for hem. Inroducion As defined in he IT infrasrucure library (ITIL, []), change managemen is a disciplined process for inroducing required changes ono he IT environmen. A good and effecive change managemen process mus minimize disrupions o he business services as a resul of performing IT changes. The main driver for IT organisaions o adop ITIL is he need o improve service qualiy [2]. Change managemen has a direc impac on service qualiy as i ries o undersand and reduce risks. This makes change managemen a major ITIL process, ofen implemened early on when adoping ITIL, alongside inciden managemen and configuraion managemen. Our research agenda in change managemen is driven by he resuls of a survey wih IT change managers and praciioners in 2006 [3]. The survey highlighed ha currenly, he op hree problems in change managemen are: ) scheduling and planning of changes, 2) handling high number of urgen changes, and 3) dealing wih ill-definiion of reques for changes. To respond o hese challenges, we have projecs underway on assessmen of risk in change managemen, on assised design of changes and on business-driven scheduling of changes. In his wor we formalize he change scheduling as an opimizaion problem and we develop mehods o solve i o opimaliy. We build on our previous work by exending our concepual model for change scheduling and breaking down he changes ino he aciviies ha compose hem. As an example, we reuse he calculaion of business impac defined in [5] and use i as he objecive funcion of he opimizaion problem. A.K. Bandara and M. Burgess (Eds.): AIMS 2007, LNCS 4543, pp , Springer-Verlag Berlin Heidelberg 2007

3 74 D. Trasour, M. Rahmoun and C. Barolini The problem wih scheduling changes is ha IT praciioners have lile visibiliy ino business risk and impac of changes ono cusomers. In order o make as much informaion as possible ransparenly available o all he sakeholders, ITIL recommends he creaion of a change advisory board (CAB). The ypical CAB is made up of decision-makers from IT operaions, applicaion eams, and business unis usually dozens of people who mee weekly o review change requess, evaluae risks, idenify impacs, accep or rejec changes, and prioriize and schedule he ones hey approve. However, CAB meeings are usually long and edious and consume a grea amoun of ime ha could be made available o deal wih change building, esing and deploymen, wih consequen benefi for he IT organizaion s efficiency. The problem is furher complicaed by he ever increasing number of changes and he consanly growing complexiy of IT infrasrucure. I is no uncommon for CABs o receive several hundreds of changes per week (such volume of change has been observed in HP ousourcing cusomers). Besides he negaive impac on efficiency imposed by CAB meeings, various oher facors impac he effeciveness of he change managemen process, he effec of which could be miigaed by careful scheduling: because of he complexiy of infrasrucures and he number of possible sakeholders, CABs can accuraely idenify change collisions ha occur when wo simulaneous changes impac he same resource or applicaion; i is difficul o undersand cross-organizaion schedules since large organizaions have muliple CABs wih no coordinaion beween hem. In his paper, we discuss how our approach o aciviy-based scheduling of IT changes allows us o ackle hese problems. The remainder of his paper is srucured as follows. In secion 2 we inroduce conceps and design relevan daa srucures ha are he bases for he formalizaion of he aciviy-based change scheduling problem (presened in secion 3). In secion 4 we provide experimenal validaion of he approach. We discuss relaed work in secion 5 and draw our conclusions in secion 6. 2 Relaed Work Our work belongs o he research domain in IT service managemen, and in paricular of business-driven IT managemen (BDIM). For a comprehensive review of business-it managemen, see [9]. The research in Business-driven IT managemen covers auomaion and decision suppor for IT managemen processes, driven by he objecives of he business. The novely of he work presened here, (as well as for [5] ha preceded i), is ha our approach arges he dimensions of people and processes in IT managemen raher han he echnology dimension of i as he mos noable early effors in businessdriven IT managemen do, in paricular he ones ha were applied o (see [9,0,,2,3,8] for service level managemen, [2,4,5] for capaciy managemen, and [9] for securiy managemen on he service delivery side of ITIL []).

4 Aciviy-Based Scheduling of IT Changes 75 More relevan o our line of research are BDIM works ha ouch on IT suppor processes, such as inciden managemen, problem managemen, change managemen iself and configuraion managemen. The managemen by business objecives (MBO) mehodology ha we described in [6] - and ha we applied here o inciden managemen is also he driver for his work. However, he focus of his paper is on he soluion of he scheduling problem iself, whereas in our previous paper we did lead o he formulaion of (mixed ineger programming) inciden prioriizaion problem, bu we ouched on i jus as an example of puing he MBO mehodology o work. Besides, he scheduling problem considered here reaches a far deeper level of complexiy han he inciden prioriizaion problem. Coming o change managemen, Keller s CHAMPS [7] (CHAnge Managemen wih Planning and Scheduling) is he seminal work. A a firs level of analysis, he formulaion of he scheduling problem ha we presen here can look very similar o he scheduling opimizaion problem ha CHAMPS solves. While his provide muual validaion of boh approaches, i has o be noed ha CHAMPS addresses he auomaion aspecs of he change managemen process and deals in paricular wih sofware deploymen, whereas in his work we look a scheduling as a decision problem, offering suppor for negoiaion of he forward schedule of change in CAB (change advisory board) meeings. In paricular, CHAMPS assigns aciviies o servers, whereas in our formulaion aciviies are assigned o echnicians and affec configuraion iems. Anoher significan difference in he wo approaches is ha his work akes ino accoun he IT service model: hardware componens, applicaions and services and heir dependencies. This allows us o model and avoid conflics beween changes. Wih respec o our previous wor in [4] we inroduced a mahemaical formulaion of he business impac of performing IT changes. In [5], we presened a concepual model of change scheduling and evaluaed he business impac of a change schedule. While he algorihm presened in [5] was only dealing wih assigning changes o change windows, here we ake he scheduling problem o he nex level of deail, by acually scheduling down o he level of he single change aciviies composing he change, and producing deailed schedules for mainenance windows. [5] also concenraed on providing a plausible business-oriened uiliy funcion o maximize, whereas here we are here agnosic as far as he objecive funcion is concerned. Finally, scheduling is a field which has received a lo of aenion. A grea variey of scheduling problems [20] have been sudied and many soluion mehods have been used. Saff scheduling problems in paricular have been well sudied [Erns]. Our problem can be seen as a generaion of a generalized resource consrain scheduling problem [2]. Our problem has he addiional difficuly ha one need o avoid conflicing change aciviies on IT componens. 3 Change Scheduling As seen in he inroducion, CAB members need o have up-o-dae change informaion o be able o make good decisions. Such informaion includes he deailed designs of changes, he opology of he underlying IT infrasrucure and services, he

5 76 D. Trasour, M. Rahmoun and C. Barolini calendars of change implemeners. We now briefly recall he secions of he concepual model presened in [5] ha are relevan o our more deailed problem descripion. We exend he model o include he noion of change aciviies. We hen move on o presening he mahemaical formalizaion of he aciviy-based scheduling problem. We firs need a model of he IT services ha are under change conrol. ITIL calls configuraion iem any componen of he IT infrasrucure (hardware or sofware) ha is required o deliver a service. The configuraion managemen daabase (CMDB) holds he collecion of configuraion iems, along wih heir dependencies. We model he CMDB as a direced graph where he nodes are configuraion iems and where edges represen direc dependencies beween configuraion iems. Such dependencies can be conainmen dependencies (i.e. a web server insance runs a given server) or logical dependencies (i.e. a J2EE applicaion depends on a daabase server). A reques for change (RFC) represens a formal proposal for a change o be made. The RFC conains a high-level exual descripion of he change. I also specifies an implemenaion deadline, by which he change mus be implemened. Penalies may apply if no. During he planning phase of he change managemen process, he high-level descripion of he change conained in he RFC is refined ino a concree implemenaion plan. The implemenaion plan describes he collecion of aciviies and resources (people, echnology, processes) ha are required o implemen he change. The plan also specifies dependency consrains beween aciviies. As commonly done in projec managemen [6], he dependency consrains are expressed in he form of a lag ime and a dependency ype, finish-before-sar, sar-beforefinish, finish-before-finish or sar-before-sar consrains. A change aciviy represens an elemenary acion ha mus be performed in order o complee a sep of he change implemenaion. An aciviy has an associaed expeced duraion and requires a se of implemenaion resources. As seen previously, i migh also depend on oher aciviies. Finally, a change aciviy may affec one or more configuraion iems. An implemenaion resource is any echnical resource ha is required o perform a change aciviy, such as a change implemener or a sofware agen. Our model aaches an hourly cos o each implemenaion resource. Finally, change windows are pre-agreed periods of ime during which mainenance can be performed for an IT service. Such windows are usually found in service level agreemens (SLA) or operaing level agreemens (OLA). Wih his concepual model in mind, we can define he aciviy-based scheduling problem. Our soluion o he problem consiss of wo phases. In he firs phase, changes are assigned o pre-defined change windows. This is modeled in figure wih he change window assignmen associaion. In he second phase, aciviies are assigned o implemenaion resources wihin each change windows, and his resuls in an assignmens being creaed. If we look a he aciviy-based scheduling problem as an opimizaion problem, several objecive funcions can be considered: minimizing he oal cos of implemening changes, maximizing he number of changes o implemen or minimizing he downime of cerain applicaions. We horoughly discussed alernaive objecive funcions definiion in [5]

6 Aciviy-Based Scheduling of IT Changes 77 Fig.. Change scheduling concepual model and will no go ino nearly as much deail in his paper. However, he objecive funcion does play a role in he mahemaical formulaion of he problem, and we will cover i from his poin of view in he following secion 4 Mahemaical Formulaion of he Aciviy-Based Change Scheduling Problem Le C = { ci : i N} be he se of changes ha have been designed, buil and esed and are ready o be scheduled. Each change c i is composed of a se of aciviies A i = { a j : j A i }, where each aciviy a i, j has an esimaed duraion δ j. The scheduling of changes is done over a given ime horizon. Le W be he number of predefined change windows w : w W ha are pre-allocaed wihin his ime horizon. We refer o ime wihin each change window hrough he index : 0 < Δw. Le { r k : k R} be he se of implemenaion resources ha are necessary o implemen changes. Le κ k, be he capaciy of resource r k a ime in window w. This capaciy allows us o model boh he availabiliy of a resource (when κ = 0 he resource is unavailable) and he degree of parallelism of a given resource (a resource can perform up o κ k, aciviies in parallel). Le ρ j be he se of resources ha are necessary o implemen aciviy a i, j. To represen conflics beween changes, we also need a model of he service hierarchy and of he configuraion iems ha are being changed. Le { : l I} be i l

7 78 D. Trasour, M. Rahmoun and C. Barolini he se of configuraion iems. Le A ~ l be he se of aciviies ha direcly impac configuraion iem i l. Le D l be he se of configuraion iems ha depend on i l (i.e. he ransiive closure of is direc dependans). Possible soluions o he scheduling problem are characerized by he binary variables u i, w and x i,. The variables have he following meaning: u i, w is equal o if change c i is scheduled in change window w, and is equal o 0 oherwise. x is equal o if he implemenaion of aciviy a i, j by he resource r k sars in change window w a ime and is equal o 0 oherwise. Finally he variables l l, will be used o represen resource locking in order o avoid conflic; more specifically l l, is equal o when he configuraion iem i l is locked by a change aciviy a ime in change window w. We now model he consrains of he problem. When omied, he ranges for each index are as follows: i : i N, j : j Ai, k : k R, w : w W, : 0 i < Δ, and l : i I. w W l= u k i () x A R T i w i x = ui k. ρ i j w (2), j= k= = j= = 0 A w : Δ w δ j + < Δ Equaion () ensures ha each change is execued a mos once. In equaion (2) we make sure ha if a change is scheduled o be execued in a change windo hen all he aciviies ha i comprises of are implemened wihin ha change window. This also ensures ha a change canno span several change windows, which is undesirable as his siuaion would leave he infrasrucure in an unknown sae and would likely resul in service unavailabiliy. Equaion (3) ensures ha any aciviy ha is sared in a change window is compleed wihin he bounds of he change window., w k : k ρ Tw x = u w = 0 j w (3) (4) x k, = 0 k : k ρ j (5)

8 Aciviy-Based Scheduling of IT Changes 79 Equaions (4) and (5) guaranee ha he appropriae resources are used in he implemenaion of each aciviy. In paricular, (4) saes ha if he change is scheduled for a given windo hen someime during ha window all he necessary resources are scheduled o sar working on i. Conversely, (5) prevens his from happening if he for he resources ha are no required. As far as capaciy consrains are concerned, heir expression in erms of he u i, w and x i, variables does no come naurally. However, we observe ha hey can naurally be expressed via a binary variable signaling when an aciviy is being execued (recall ha x only specifies when he aciviy sars). To his end, we inroduce he auxiliary variable z, whose value is a all ime during aciviy execuion and 0 oherwise. z is in urn bes calculaed hrough he inroducion of wo more auxiliary variables: s, ha is indefiniely equal o afer he aciviy sared and 0 oherwise; and f, ha is indefiniely equal o afer he aciviy finished and 0 oherwise. s f k, k, = x τ = 0 δi, j = τ = 0 k, x k, w τ (6), τ (7) z = s f (8) The inerpreaion of hese auxiliary variables is bes undersood graphically, as shown in he able below. x s k, f z Table. Illusraion of problem variables for an aciviy of duraion Capaciy consrains can now be quie naurally expressed: N Ai i= j= z,,,, κ,, (9) i j k w k w

9 80 D. Trasour, M. Rahmoun and C. Barolini The auxiliary variable f and s come very useful also when specifying precedence consrains beween change aciviies. For example, we can naurally express a finishbefore-sar precedence consrain beween wo aciviies a j and a j 2 wih equaion (0). λ represen an addiional lag ha can be modeled if needed. j, j2 W Tw w= = 0 f j, k, s j, λ j, j (0) 2 2 Sar-before-finish, sar-before-sar and finish-before-finish consrains are expressed hrough similar linear composiions of s and f. The following consrains deal wih he possibiliy of conflicing change aciviies on he infrasrucure. ρ R ~ a A i j i j,, l k =. z = l l, l, () ll, ll, l, l : l Dl, (2) Equaion () ensures ha he lock l l, is se and ha, among he aciviies ha have an effec on he configuraion iem i l, only one aciviy is acive a a ime (possibly using several resources ρ j ). Equaion (2) saes ha all dependen configuraion iems D l are affeced when he configuraion iem i l is being worked on. Oher addiional consrains can be imposed o make he model work in a pracical seing. For example, one could require o have a minimum number of changes scheduled (i.e. 90% of changes mus be scheduled). Or change managers and supervisors may wan o resric some changes o ake place wihin cerain given change windows, or o resric he permissible schedules of some aciviies in oher ways. The expression of hese addiional consrains lends iself quie usefully o he case in which only a marginal re-scheduling is necessary due o he incumbency of some changes. In his case, he user may wan o preven re-scheduling of changes whose implemenaion dae is approaching. All hese consrains can be naurally expressed hrough linear combinaions of he u i, w and x. In order for he problem formulaion o be complee, we now express is objecive funcion. Depending on he requiremens of he change managers and supervisors, differen insances of objecive funcion could be used. As an example, when we minimize he oal cos of implemening changes, including he esimaed business impac [4], he objecive funcion becomes: W N minimize φ u (3) w= i= w. w

10 Aciviy-Based Scheduling of IT Changes 8 This complees he heoreical developmen of he aciviy-based change scheduling problem. In he nex secion we will discuss experimenal validaion of he mehod described here. 5 Experimenal Validaion We have implemened he mahemaical programming formulaion presened in his paper using CPLEX [7]. Due o he complexiy of he problem definiion, i urns ou ha in he wors case scenario our formulaion does no scale up o a number of changes in he order of he hundreds. This formulaion has however been a valuable insrumen o beer undersand user requiremens, as i allowed us o quickly capure and es addiional user consrains, and o compare alernaive objecive funcions such as he minimizaion of he makespan or of he number of conflics. For pracical applicaions of he algorihm, we herefore need o develop heurisic soluions, while we will sill use he complee formulaion o validae he accuracy of he heurisics for low-dimension cases. We herefore developed a prioriy-based lis scheduler [8] where he business impac plays he role of he prioriy funcion. To compare he performance of he wo implemenaions and o gauge he qualiy of he soluions produced by he prioriy-based lis scheduler, we have developed a random generaor of changes and resources. The generaor akes as inpu: he number of change requess submied per day, he average number of aciviies per change, he number of managed services, he number of configuraion iems and he number of available implemeners. The changes and resources generaor produces he following: service model along wih he dependencies beween configuraion iems; service level agreemen penalies; for each change, is ype (emergency, rouine and normal) and is implemenaion deadline. For example, he deadline of an emergency change is se o 2 o 4 days from is submission dae on average; for each change, is reference random plan, modeled as a dependency graph beween aciviies; for each aciviy, is duraion, is required locks on configuraion iem and is required resources. We have run series of experimens comparing boh implemenaions wih differen loads of changes and resources. We have fixed he number of services o 20, he number of configuraion iems o 00, he average number of aciviies per change o 5 and we varied he number of changes and he number of resources as shown in Table 2. Table 2. Experimens wih varying load Aciviies per Change Changes CIs Services Resources Example Example Example Example

11 82 D. Trasour, M. Rahmoun and C. Barolini The resuls of our experimens are shown in Table 3. Boh algorihms were run on an HP Worksaion XW8200 wih a 3.2 GHz Xeon processor and 2GB RAM. For each implemenaion, Table 3 shows he processing ime needed o schedule he examples defined in Table 2 as well as he esimaed overall business impac. The business impac of assigning a change o a change window is calculaed by summing up he following hree componens:. Cos of implemening he change: each resource has an hourly rae 2. Poenial revenue loss: esimaed loss in revenue due o he degradaion of services impaced by he change. 3. Penalies incurred from he violaion of service level agreemens including penalies for missing deadlines. Table 3. Comparison beween PLS and CPLEX implemenaions Prioriy lis scheduler CPLEX scheduler Processing Time Overall Impac Processing Time Overall Impac Example 0.5 sec $24 K 40 sec $8K Example 2 8 sec $55K 4hours $70K Example 3 97 sec $376K ** ** Example 4 53 sec $948K ** ** For low-dimension examples (less han a hundred changes), he CPLEX scheduler produces he opimal soluion wihin an accepable ime. As he number of changes ges bigger, he processing ime grows exponenially, making i impossible o apply i o real IT environmens (housands of changes per monh). In examples 3 and 4, he scheduler ran over 2 hours wihou producing a resul while he lis scheduler ook less han 0 minues. Through analyzing he resuls produced by boh implemenaions for small examples, here are some improvemens ha could be made o he lis scheduler for producing beer resuls. One improvemen is o ry o fi more changes ino each change window by scheduling aciviies wih smaller mobiliy (disance beween is earlies possible assignmen and is laes possible assignmen) firs, while giving prioriy o he highes impaced changes. Anoher improvemen would be o sor he changes no according o heir impac over one change window bu over wo or more change windows. As an example, le s ake wo changes c and c2 and wo change windows cw and cw2 and le s assume ha he impac of assigning: c o cw is $0K c o cw2 is $5K c2 o cw is $8K c2 o cw2 is $24K If we assign c o cw and c2 and cw2, he overall impac is $34K, bu if we assign c2 o cw and c o cw2, he overall impac is $23K.

12 Aciviy-Based Scheduling of IT Changes 83 6 Conclusions Building on an earlier mahemaical formulaion of he change scheduling problem, in his paper we presened a mehodology and a ool which pushes he formalizaion of he problem o he nex level of deail, by breaking down he changes ino he aciviies ha compose hem. We illusraed he heoreical viabiliy of he approach, discuss he limi of is applicabiliy o real life scenarios, describe heurisic echniques ha promise o bridge he scalabiliy gap and provide experimenal validaion for hem. In conducing our experimens and showing he prooype o domain expers, i emerged ha end users would found i difficul o deal wih schedules ha are auomaically generaed. The ool we have produced assumes ha he knowledge regarding change aciviies is complee and accurae. This is no necessarily he case in a producion environmen and may lead o problemaic schedules. Raher han having a fully auomaed procedure, domain expers expressed he need o incremenally schedule ses of changes and o preserve pre-exising assignmens as much as possible. They also recommended ha all consrains should no be reaed wih he same imporance and ha some consrains should be relaxed based on preferences and user feedback. Our immediae nex seps are o address hese issues. Furher along our research pah we plan o ake ino accoun he fac ha changes may fail during he course of heir implemenaion, hereby possibly invalidaing curren schedules. We will do so by accommodaing for back-ou change plans in our schedule. The challenge ahead of us is ha o indiscriminaely accoun for each and every change failure in our models will mos likely be overkill. Techniques assessing he likelihood of a change o fail given pas hisory and presen condiions look like a promising avenue o assess risk of failure and only scheduling for possible back-ou if he change has a non-negligible likelihood of failing. References. IT Infrasrucure Library, ITIL Service Delivery and ITIL Service Suppor, Office of Governmen Commerce, UK (2003) 2. ITIL Change Managemen Mauriy Benchmark Sudy, Whie Paper, Evergreen, hp:// 3. The Boom Line Projec. IT Change Managemen Challenges Resuls of 2006 Web Survey, Technical Repor DSC005-06, Compuing Sysems Deparmen, Federal Universiy of Campina Grande, Brazil (2006) 4. Sauvé, J., Rebouças, R., Moura, A., Barolin C., Boulmakoul, A., Trasour, D.: Businessdriven suppor for change managemen: planning and scheduling of changes. In: Sae, R., van der Meer, S., O Sullivan, D., Pfeifer, T. (eds.) DSOM LNCS, vol. 4269, pp Springer, Heidelberg (2006) 5. Rebouças, R., Sauvé, J., Moura, A., Barolin C., Boulmakoul, A., Trasour, D.: A decision suppor ool o opimize scheduling of IT changes. In: Proc. 0h IFIP/IEEE Symposium on Inegraed Managemen (IM2007), Munich (May 2007) 6. Elmaghraby, E., Kamburowsk J.: The Analysis of Aciviy Neworks under Generalized Precedence Relaions (GPRs). Salah Managemen Science 38(9), (992) 7. ILOG Inc, ILOG CPLEX 0. user s manual and reference manual

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